Marker sequences for diagnosing and stratifying SLE patients

The present invention relates to methods for identifying markers for systemic lupus erythematosus (SLE) and to the markers identified with the aid of this method, which can differentiate between SLE and other autoimmune diseases on the one hand and between different SLE subgroups on the other hand. The invention also relates to panels, diagnostic devices and test kits which comprise these markers, and to the use and application thereof, for example for the diagnosis, prognosis and therapy control in SLE. The invention also relates to methods for screening and validating active substances for application in SLE subgroups.

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Description
RELATED APPLICATIONS

This application is a national stage application (under 35 U.S.C. § 371) of PCT/EP2015/052805, filed Feb. 10, 2015, which claims benefit of European Application No. 14154557.4, filed Feb. 10, 2014, and European Application No. 14178090.8, filed Jul. 22, 2014.

SUBMISSION OF SEQUENCE LISTING

The Sequence Listing associated with this application is filed in electronic format via EFS-Web and hereby incorporated by reference into the specification in its entirety. The name of the text file containing the Sequence Listing is Sequence Listing_074027_0034. The size of the text file is 6,394 KB, and the text file was created on Nov. 30, 2016.

The present invention relates to methods for identifying markers for systemic lupus erythematosus (SLE) and to the markers identified with the aid of this method, which can differentiate between SLE and other autoimmune diseases on the one hand and between different SLE subgroups on the other hand. The invention also relates to panels of markers for SLE, diagnostic devices and test kits for SLE which comprise these markers, and to the use and application thereof, for example for the diagnosis, prognosis and therapy control of SLE. The invention also relates to methods for screening and for validating active substances for application in SLE subgroups.

Systemic lupus erythematosus (SLE) is a rare autoimmune disease. In the case of lupus erythematosus the body's own immune system is disregulated. It not only attacks bacteria, viruses and cancer cells, but also healthy body cells. Organs and organ systems, for example the skin, are damaged as a result.

In clinical practice, SLE is diagnosed on the basis of a combination of clinical and immunological parameters. Here, antinuclear autoantibodies (ANAs) and anti-double-stranded DNA (anti-dsDNA) autoantibodies play a key role. However, the ANA test is not specific for SLE, since other autoimmune diseases and up to 20% of healthy individuals are also positively tested. The autoreactivity against extractable nuclear antigens (ENAs) as recombinant or purified individual antigens is therefore increasingly tested, for example against Sm-protein, U1-RNP, Rho52/SS-A and Ro60/SS-B. These antigens and associated autoantibodies, however, are not sufficient for diagnosing all SLE patients without doubt, in particular in an early phase of the disease. By way of example, anti-dsDNA antibodies are indeed highly specific for SLE and can be detected in approximately 70% of patients. However, the titre of the anti-dsDNA antibodies correlates with the disease activity in some patients, but not in all patients. As a result, SLE is often only diagnosed months or years after the occurrence of the first symptoms. A further problem of the currently used diagnostic methods is that the suitability of the previously tested autoantigens for the diagnosis of organ involvement and complications is disputed, and partly conflicting data has been published.

There is thus a great need to provide new markers for the diagnosis and differential diagnosis of SLE.

Marker sequences for the diagnosis of SLE are disclosed in WO 2012/049225 A2. These marker sequences were discovered by a method in which serum samples of SLE patients and those of healthy individuals were examined by comparison and the results were statistically evaluated. The marker sequences described in WO 2012/049225 A2, however, are not sufficiently suitable for the diagnosis of SLE with regard to a distinction from other autoimmune diseases and the identification of SLE subgroups.

There is therefore still a need for markers for SLE, in particular for the distinction of SLE from other autoimmune diseases.

This object has been achieved in accordance with the invention in that a differential method comprising a multiplicity of steps has been developed, in which serum samples of healthy individuals and patients with various autoimmune diseases were examined by comparison with regard to their reactivity with a multiplicity of potential antigens and these results were statistically evaluated. The selection of the serum samples and the sequence of the steps surprisingly made it possible to identify highly specific markers for SLE which are also suitable for identifying SLE subgroups and complications such as lupus nephritis and for providing a differential diagnosis in respect of other autoimmune diseases, such as rheumatoid arthritis (RA), systemic sclerosis (SSc), ankylosing spondylitis or Bekhterev's disease (SPA), and also in respect of individuals who have early RA, i.e. have been suffering with the disease for less than two years (“patients with early RA”).

The present invention relates to a method for identifying markers for systemic lupus erythematosus (SLE) comprising the following steps

    • a) bringing serum samples of SLE patients into contact with more than 5000 antigens coupled to (Luminex) beads, measuring the binding of the individual antigens to proteins, in particular autoantibodies, in the serum of the SLE patients by means of immunofluorescence assay, and determining the median fluorescence intensity (MFI) for each individual antigen;
    • b) bringing serum samples of patients with rheumatoid arthritis (RA) into contact with the same antigens coupled to (Luminex) beads, measuring the binding of the individual antigens to proteins, in particular autoantibodies, in the serum of the RA patients by means of immunofluorescence assay, and determining from this the median fluorescence intensity (MFI) for each individual antigen;
    • c) bringing serum samples of healthy individuals into contact with the same antigens coupled to (Luminex) beads, measuring the binding of the individual antigens to proteins, in particular autoantibodies, in the serum of the healthy individuals by means of immunofluorescence assay, and determining from this the median fluorescence intensity (MFI) for each individual antigen;
    • d) statistically evaluating the MFI data from a), b) and c) by means of univariate analysis and thus identifying marker candidate antigens with which SLE patients can be differentiated from RA patients and from healthy individuals;
    • e) bringing serum samples of patients with early RA into contact with the marker candidate antigens identified in d) coupled to (Luminex) beads, measuring the binding of marker candidate antigens to proteins, in particular autoantibodies, in the serum of patients with early RA by means of immunofluorescence assay, and determining from this the median fluorescence intensity (MFI) for each marker candidate antigen;
    • f) bringing serum samples of patients with systemic sclerosis (SSc patients) into contact with the marker candidate antigens identified in d) coupled to (Luminex) beads, measuring the binding of marker candidate antigens to proteins, in particular autoantibodies, in the serum of SSc patients by immunofluorescence assay, and determining from this the median fluorescence intensity (MFI) for each marker candidate;
    • g) bringing serum samples of patients with ankylosing spondylitis or Bekhterev's disease (SPA patients) into contact with the marker candidate antigens identified in d) coupled to (Luminex) beads, measuring the binding of marker candidate antigens to proteins, in particular autoantibodies, in the serum of SPA patients by means of immunofluorescence assay, and determining from this the median fluorescence intensity (MFI) for each marker candidate antigen;
    • h) statistically evaluating the MFI data from e), f) and g) by means of univariate analysis and, when a threshold value of 3 standard deviations above the mean value of the healthy samples is not reached, identifying a specific marker for SLE, wherein the markers are selected from sequences SEQ ID No. 1 to 1584, homologues of sequences SEQ ID No. 1 to 1584 with at least 95% homology, subsequences of SEQ ID No. 1 to 1584, subsequences of homologues of SEQ ID No. 1 to 1584 with at least 95% homology.

The term “systemic lupus erythematosus (SLE) relates to a systemic autoimmune disease from the group of collagenoses. What is known as the butterfly rash is particularly characteristic for SLE (systemic lupus erythematosus). The diagnosis criteria for SLE are:

1. butterfly rash, 2. discoid skin changes, 3. sensitivity to light, 4. mucous membrane ulcers (generally painless), 5. arthritis in at least two joints, 6. serositis (pleurisy or pericarditis), 7. kidney involvement (proteinuria >0.5 g/d or cylinder), 8. CNS involvement (cramps or psychosis), 9. haematological findings (haemolytic anaemia, leucopenia or thrombopenia), 10. immunological findings (anti-dsDNA antibodies, anti-Sm antibodies, anticardiolipin antibodies), 11. antinuclear antibodies without taking lupus erythematosus-triggering medication.

Evaluation: With four (three) positive findings, the diagnosis is considered reliable (likely) (definition for example according to Pschyrembel, de Gruyter, 261st edition (2007), Berlin).

One embodiment of the invention relates to methods for identifying markers for SLE which are suitable for the diagnosis and differential diagnosis of SLE, in particular for distinction from other autoimmune diseases, preferably for distinction from other rheumatic diseases, particularly preferably for distinction from RA, SSc, and SPA. These markers are also suitable for distinction from patients with early RA. These markers for SLE according to the invention are the subject of group 1 of antigens in Table 2, which can be used for the diagnosis of SLE. For the generation of these markers, marker candidate antigens which have an adjusted p-value for the non-parametric mean value comparison between groups of <0.05 and at the same time a fold change of >1.5 and additionally an AUC resulting from the ROC analysis of >0.75 are selected on the basis of the univariate results. In addition, the ENA-4 antigens are selected. For this pool of selected marker candidate antigens, an L1-penalised logistic regression model is preferably also established within the scope of a nested cross validation. Marker candidate antigens which are not considered within the scope of the creation of the model are removed from the further consideration. The markers for SLE are thus obtained, selected from the sequences (group 1)

SEQ ID No. 1 to 24, 134, 168, 213, 367 to 369 SEQ ID No. 528 to 551, 661, 695, 741, 895 to 897 and SEQ ID No. 1057 to 1080, 1190, 1224, 1270, 1424 to 1426,

homologues of SEQ ID No. 1 to 24, 134, 168, 213, 367 to 369 SEQ ID No. 528 to 551, 661, 695, 741, 895 to 897 and SEQ ID No. 1057 to 1080, 1190, 1224, 1270, 1424 to 1426 with at least 95% homology, subsequences of SEQ ID No. 1 to 24, 134, 168, 213, 367 to 369 SEQ ID No. 528 to 551, 661, 695, 741, 895 to 897 and SEQ ID No. 1057 to 1080, 1190, 1224, 1270, 1424 to 1426 and subsequences of homologues of SEQ ID No. 1 to 24, 134, 168, 213, 367 to 369 SEQ ID No. 528 to 551, 661, 695, 741, 895 to 897 and SEQ ID No. 1057 to 1080, 1190, 1224, 1270, 1424 to 1426 with at least 95% homology.

Another embodiment relates to methods for identifying markers for the subgroup of SLE patients with the complication lupus nephritis, comprising the comparison of the autoantibody profiles of SLE patients with lupus nephritis with those of SLE patients without lupus nephritis. Markers which are found by means of this embodiment of the method are specified for example in Table 2, in group 2 and group 5. These are methods for example in which the markers for the subgroup of the SLE patients with the complication lupus nephritis are selected from the sequences

SEQ ID No. 25 to 54, 214, 215, 216, 217, 227, 232, 240, 244, 246, 248, 257, 287, 288, 300, 308, 314, 315, 323, 329, 330, 336, 338, 347, 349, 358, 361, 362,

SEQ ID No. 552 to 581, 742, 743, 744, 745, 755, 760, 768, 772, 774, 776, 785, 815, 816, 828, 836, 842, 843, 851, 857, 858, 864, 866, 875, 877, 886, 889, 890 and

SEQ ID No. 1081 to 1110, 1271, 1272, 1273, 1274, 1284, 1289, 1297, 1301, 1303, 1305, 1314, 1344, 1345, 1357, 1365, 1371, 1372, 1380, 1386, 1387, 1393, 1395, 1404, 1406, 1415, 1418, 1419,

homologues of SEQ ID No. 25 to 54, 214, 215, 216, 217, 227, 232, 240, 244, 246, 248, 257, 287, 288, 300, 308, 314, 315, 323, 329, 330, 336, 338, 347, 349, 358, 361, 362,

SEQ ID No. 552 to 581, 742, 743, 744, 745, 755, 760, 768, 772, 774, 776, 785, 815, 816, 828, 836, 842, 843, 851, 857, 858, 864, 866, 875, 877, 886, 889, 890 and

SEQ ID No. 1081 to 1110, 1271, 1272, 1273, 1274, 1284, 1289, 1297, 1301, 1303, 1305, 1314, 1344, 1345, 1357, 1365, 1371, 1372, 1380, 1386, 1387, 1393, 1395, 1404, 1406, 1415, 1418, 1419 with at least 95% homology, subsequences of SEQ ID No. 25 to 54, 214, 215, 216, 217, 227, 232, 240, 244, 246, 248, 257, 287, 288, 300, 308, 314, 315, 323, 329, 330, 336, 338, 347, 349, 358, 361, 362, SEQ ID No. 552 to 581, 742, 743, 744, 745, 755, 760, 768, 772, 774, 776, 785, 815, 816, 828, 836, 842, 843, 851, 857, 858, 864, 866, 875, 877, 886, 889, 890 and SEQ ID No. 1081 to 1110, 1271, 1272, 1273, 1274, 1284, 1289, 1297, 1301, 1303, 1305, 1314, 1344, 1345, 1357, 1365, 1371, 1372, 1380, 1386, 1387, 1393, 1395, 1404, 1406, 1415, 1418, 1419 and subsequences of homologues of SEQ ID No. 25 to 54, 214, 215, 216, 217, 227, 232, 240, 244, 246, 248, 257, 287, 288, 300, 308, 314, 315, 323, 329, 330, 336, 338, 347, 349, 358, 361, 362, SEQ ID No. 552 to 581, 742, 743, 744, 745, 755, 760, 768, 772, 774, 776, 785, 815, 816, 828, 836, 842, 843, 851, 857, 858, 864, 866, 875, 877, 886, 889, 890 and SEQ ID No. 1081 to 1110, 1271, 1272, 1273, 1274, 1284, 1289, 1297, 1301, 1303, 1305, 1314, 1344, 1345, 1357, 1365, 1371, 1372, 1380, 1386, 1387, 1393, 1395, 1404, 1406, 1415, 1418, 1419 with at least 95% homology.

A further embodiment relates to methods which comprise the statistical evaluation by means of an L1-penalised logistic regression model with five-fold cross validation and twenty times repetition and selection of the markers which occur at a frequency of 50% or more. Markers which can be identified by means of this embodiment of the method are specified for example in Table 2, group 2. These are methods for example in which the markers for the subgroup of the SLE patients with the complication lupus nephritis are selected from the sequences

SEQ ID No. 25 to 54, SEQ ID No. 552 to 581 and SEQ ID No. 1081 to 1110,

homologues of 25 to 54, SEQ ID No. 552 to 581 and SEQ ID No. 1081 to 1110 with at least 95% homology, subsequences of SEQ ID No. 25 to 54, SEQ ID No. 552 to 581 and SEQ ID No. 1081 to 1110 and subsequences of homologues of SEQ ID No. 25 to 54, SEQ ID No. 552 to 581 and SEQ ID No. 1081 to 1110 with at least 95% homology.

In a further embodiment of the method, markers for defined subgroups of SLE patients are identified in that the sequences SEQ ID No. 1 to 527 (clone sequences) are correlated with one of the sequences SEQ ID No. 1 to 527 by calculation of the Spearman's rank correlation coefficient for the particular marker. In this way, the markers of groups 1, 2 and 3 in Table 2 can be identified with the method according to the invention, for example. These are methods for example in which the markers which demonstrate a correlation with one another of the reactivities in SLE patients are selected from the sequences (group 3)

SEQ ID No. 55 to 111, SEQ ID No. 582 to 1005 and SEQ ID No. 1111 to 1167,

homologues of SEQ ID No. 55 to 111, SEQ ID No. 582 to 1005 and SEQ ID No. 1111 to 1167 with at least 95% homology, subsequences of SEQ ID No. 55 to 111, SEQ ID No. 582 to 1005 and SEQ ID No. 1111 to 1167 and subsequences of homologues of SEQ ID No. 55 to 111, SEQ ID No. 582 to 1005 and SEQ ID No. 1111 to 1167 with at least 95% homology and from the sequences (group 2)

SEQ ID No. 25 to 54, SEQ ID No. 552 to 581 and SEQ ID No. 1081 to 1110,

homologues of SEQ ID No. 25 to 54, SEQ ID No. 552 to 581 and SEQ ID No. 1081 to 1110 with at least 95% homology, subsequences of SEQ ID No. 25 to 54, SEQ ID No. 552 to 581 and SEQ ID No. 1081 to 1110 and subsequences of homologues of SEQ ID No. 25 to 54, SEQ ID No. 552 to 581 and SEQ ID No. 1081 to 1110 with at least 95% homology and from the sequences (group 1)

SEQ ID No. 1 to 24, 134, 168, 213, 367 to 369 SEQ ID No. 528 to 551, 661, 695, 741, 895 to 897 and SEQ ID No. 1057 to 1080, 1190, 1224, 1270, 1424 to 1426,

homologues of SEQ ID No. 1 to 24, 134, 168, 213, 367 to 369 SEQ ID No. 528 to 551, 661, 695, 741, 895 to 897 and SEQ ID No. 1057 to 1080, 1190, 1224, 1270, 1424 to 1426 with at least 95% homology, subsequences of SEQ ID No. 1 to 24, 134, 168, 213, 367 to 369 SEQ ID No. 528 to 551, 661, 695, 741, 895 to 897 and SEQ ID No. 1057 to 1080, 1190, 1224, 1270, 1424 to 1426 and subsequences of homologues of SEQ ID No. 1 to 24, 134, 168, 213, 367 to 369 SEQ ID No. 528 to 551, 661, 695, 741, 895 to 897 and SEQ ID No. 1057 to 1080, 1190, 1224, 1270, 1424 to 1426 with at least 95% homology.

One embodiment of the invention relates to methods for identifying markers for the subgroup of ENA-4-negative SLE patients. This embodiment of the method for example comprises the testing of the serum samples of SLE patients for the absence of autoantibodies against the extractable nuclear antigens Sm-protein, U1-RNP, Rho52/SS-A and Ro60/SS-B. By way of example, the markers of group 4, Table 2 can thus be identified. These are methods for example in which the markers for ENA-4-negative SLE patients are selected from the sequences (group 4)

SEQ ID No. 112 to 213 and 278, SEQ ID No. 639 to 741 and 806 and SEQ ID No. 1168 to 1270 and 1335,

homologues of SEQ ID No. 112 to 213 and 278, SEQ ID No. 639 to 741 and 806 and SEQ ID No. 1168 to 1270 and 1335 with at least 95% homology, subsequences of SEQ ID No. 112 to 213 and 278, SEQ ID No. 639 to 741 and 806 and SEQ ID No. 1168 to 1270 and 1335 and subsequences of homologues of SEQ ID No. 112 to 213 and 278, SEQ ID No. 639 to 741 and 806 and SEQ ID No. 1168 to 1270 and 1335 with at least 95% homology.

One embodiment of the invention relates to methods comprising the selection of markers which have an adjusted p-value for the non-parametric mean value comparison between groups of less than 0.05, and at the same time a fold change of greater than 1.5 and an AUC resulting from the ROC analysis of greater than 0.75. By way of example, the markers of groups 1, 4 and 6 can thus be identified. The corresponding calculations for panels of markers are specified in Table 5, in which the corresponding marker composition in the panels (arrangements) can be inferred from Table 4. These are methods for example in which the markers are selected from the sequences (group 6)

SEQ ID No. 218 to 226, 228 to 231, 233 to 239, 241, 242, 243, 245, 247, 249 to 256, 258 to 277, 279 to 286, 289 to 299, 301 to 307, 309 to 313, 316 to 322, 324 to 328, 331 to 335, 337, 339 to 346, 348, 350 to 357, 359, 360, 363 to 366,

SEQ ID No. 746 to 754, 756 to 759, 761 to 767, 769, 770, 771, 773, 775, 777 to 784, 786 to 805, 807 to 814, 817 to 827, 829 to 835, 837 to 841, 844 to 850, 851 to 855, 859 to 863, 865, 867 to 874, 876, 878 to 885, 887, 888, 891 to 894 and

SEQ ID No. 1275 to 1283, 1285 to 1288, 1290 to 1296, 1298, 1299, 1300, 1302, 1304, 1306 to 1313, 1315 to 1334, 1336 to 1343, 1346 to 1356, 1358 to 1364, 1366 to 1370, 1373 to 1379, 1380 to 1384, 1388 to 1392, 1394, 1396 to 1403, 1405, 1407 to 1414, 1416, 1418, 1420 to 1423,

homologues of SEQ ID No. 218 to 226, 228 to 231, 233 to 239, 241, 242, 243, 245, 247, 249 to 256, 258 to 277, 279 to 286, 289 to 299, 301 to 307, 309 to 313, 316 to 322, 324 to 328, 331 to 335, 337, 339 to 346, 348, 350 to 357, 359, 360, 363 to 366, SEQ ID No. 746 to 754, 756 to 759, 761 to 767, 769, 770, 771, 773, 775, 777 to 784, 786 to 805, 807 to 814, 817 to 827, 829 to 835, 837 to 841, 844 to 850, 851 to 855, 859 to 863, 865, 867 to 874, 876, 878 to 885, 887, 888, 891 to 894, SEQ ID No. 1275 to 1283, 1285 to 1288, 1290 to 1296, 1298, 1299, 1300, 1302, 1304, 1306 to 1313, 1315 to 1334, 1336 to 1343, 1346 to 1356, 1358 to 1364, 1366 to 1370, 1373 to 1379, 1380 to 1384, 1388 to 1392, 1394, 1396 to 1403, 1405, 1407 to 1414, 1416, 1418, 1420 to 1423 with at least 95% homology, subsequences of SEQ ID No. 218 to 226, 228 to 231, 233 to 239, 241, 242, 243, 245, 247, 249 to 256, 258 to 277, 279 to 286, 289 to 299, 301 to 307, 309 to 313, 316 to 322, 324 to 328, 331 to 335, 337, 339 to 346, 348, 350 to 357, 359, 360, 363 to 366, SEQ ID No. 746 to 754, 756 to 759, 761 to 767, 769, 770, 771, 773, 775, 777 to 784, 786 to 805, 807 to 814, 817 to 827, 829 to 835, 837 to 841, 844 to 850, 851 to 855, 859 to 863, 865, 867 to 874, 876, 878 to 885, 887, 888, 891 to 894, SEQ ID No. 1275 to 1283, 1285 to 1288, 1290 to 1296, 1298, 1299, 1300, 1302, 1304, 1306 to 1313, 1315 to 1334, 1336 to 1343, 1346 to 1356, 1358 to 1364, 1366 to 1370, 1373 to 1379, 1380 to 1384, 1388 to 1392, 1394, 1396 to 1403, 1405, 1407 to 1414, 1416, 1418, 1420 to 1423 and subsequences of homologues of SEQ ID No. 218 to 226, 228 to 231, 233 to 239, 241, 242, 243, 245, 247, 249 to 256, 258 to 277, 279 to 286, 289 to 299, 301 to 307, 309 to 313, 316 to 322, 324 to 328, 331 to 335, 337, 339 to 346, 348, 350 to 357, 359, 360, 363 to 366, SEQ ID No. 746 to 754, 756 to 759, 761 to 767, 769, 770, 771, 773, 775, 777 to 784, 786 to 805, 807 to 814, 817 to 827, 829 to 835, 837 to 841, 844 to 850, 851 to 855, 859 to 863, 865, 867 to 874, 876, 878 to 885, 887, 888, 891 to 894, SEQ ID No. 1275 to 1283, 1285 to 1288, 1290 to 1296, 1298, 1299, 1300, 1302, 1304, 1306 to 1313, 1315 to 1334, 1336 to 1343, 1346 to 1356, 1358 to 1364, 1366 to 1370, 1373 to 1379, 1380 to 1384, 1388 to 1392, 1394, 1396 to 1403, 1405, 1407 to 1414, 1416, 1418, 1420 to 1423 with at least 95% homology.

Group 7 in table 2 contains a further 85 statistically significant antigens from the methods according to the invention; these are markers selected from the sequences SEQ ID No. 367 to 450, SEQ ID No. 895 to 979, SEQ ID No. 1424 to 1507, homologues of SEQ ID No. 367 to 450, SEQ ID No. 895 to 979, SEQ ID No. 1424 to 1507 with at least 95% homology, subsequences of SEQ ID No. 367 to 450, SEQ ID No. 895 to 979, SEQ ID No. 1424 to 1507 and subsequences of homologues of SEQ ID No. 367 to 450, SEQ ID No. 895 to 979, SEQ ID No. 1424 to 1507 with at least 95% homology, which can be used for the diagnosis and differential diagnosis of SLE compared with healthy individuals and other autoimmune diseases. Antigens from group 7 were also used for the calculation of biomarker combinations.

Group 8 consists of further statistically significant antigens from the methods according to the invention; markers selected from the sequences SEQ ID No. 451 to 527, SEQ ID No. 980 to 1056, SEQ ID No. 1508 to 1584, homologues of SEQ ID No. 451 to 527, SEQ ID No. 980 to 1056, SEQ ID No. 1508 to 1584 with at least 95% homology, subsequences of SEQ ID No. 451 to 527, SEQ ID No. 980 to 1056, SEQ ID No. 1508 to 1584 and subsequences of homologues of SEQ ID No. 451 to 527, SEQ ID No. 980 to 1056, SEQ ID No. 1508 to 1584 with at least 95% homology were detected and identified for the autoantibodies in SLE patients.

The invention also relates to the individual markers for SLE identified with the method according to the invention. The method concerns markers for SLE selected from the sequences SEQ ID No. 1 to 1584, homologues of sequences SEQ ID No. 1 to 1584 with at least 95% homology, subsequences of SEQ ID No. 1 to 1584 and subsequences of homologues of SEQ ID No. 1 to 1584 with at least 95% homology. The method concerns the markers of groups 1, 2, 3, 4, 5, 6, 7, 8 in Table 2, wherein the respective groups comprise the markers of the clone sequences specified in Table 2, the corresponding RNA sequences, the corresponding protein sequences, the relevant homologues with a homology of at least 95%, and the relevant subsequences. The invention relates to a marker for SLE selected from the sequences SEQ ID No. 528 to 1056 (RNA sequences), SEQ ID No. 1057 to 1584 (protein sequences). The markers according to the invention and the associated nucleic acid sequences are presented in Table 2 (SEQ ID No. of the relevant clone sequences is specified) and can be unambiguously identified by their cited database entry, for example at www.ncbi.nlm.nih.gov/, by means of their GeneID (Table 2). The sequences SEQ ID No. 1-1584 are specified in the accompanying sequence protocol, wherein SEQ ID No. 1-527 are clone sequences (cDNA), SEQ ID No. 528-1056 are RNA sequences, and SEQ ID No. 1057-1584 are protein sequences.

The invention also relates to the proteins coded by sequences SEQ ID No. 1 to 1056, the proteins coded by homologues of the sequences SEQ ID No. 1 to 1056 with at least 95% homology to the sequences SEQ ID No. 1 to 1056, the proteins coded by subsequences of SEQ ID No. 1 to 1056, the proteins coded by homologues of the subsequences of SEQ ID No. 1 to 1056 with at least 95% homology in the subsequences. In a preferred embodiment these are the proteins SEQ ID No. 1057 to 1584, homologues of the proteins with the sequences SEQ ID No. 1057 to 1584 with at least 95% homology, subsequences of SEQ ID No. 1057 to 1584, homologues of the subsequences of SEQ ID No. 1057 to 1584 with at least 95% homology.

The invention also relates to a panel of markers (also referred to as an arrangement of markers), comprising at least two different markers for SLE which are selected independently of one another from the sequences SEQ ID No. 1 to 1584, homologues of sequences SEQ ID No. 1 to 1584 with at least 95% homology, subsequences of SEQ ID No. 1 to 1584 and subsequences of homologues of SEQ ID No. 1 to 1584 with at least 95% homology. A panel of markers for SLE can comprise 2 to 20 or more, for example 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 25, 30, 40, 50, 100 or more different markers for SLE and optionally further markers, wherein the markers of SLE are selected independently of one another from the sequences SEQ ID No. 1 to 1584, homologues of sequences SEQ ID No. 1 to 1584 with at least 95% homology, subsequences of SEQ ID No. 1 to 1584 and subsequences of homologues of SEQ ID No. 1 to 1584 with at least 95% homology, and the proteins coded by the sequences.

On account of the high clinical and serological heterogeneity of the SLE disease, it is difficult to diagnose SLE unambiguously using just one biomarker. It is therefore often necessary to combine (where possible) uncorrelated autoantigens to form what are known as panels of markers (biomarker panels for SLE). By way of example, within the scope of individualised medicine, corresponding panels of markers for SLE can be composed individually for the relevant SLE subtype (subgroup) for individual patients or patient groups. It is therefore also necessary to have available a multiplicity of potential markers for SLE in order to select suitable subgroups or subtypes of specific markers for SLE for the individual case in question. A corresponding panel can be embodied for example in the form of an arrangement, an array, or also one or more beads, preferably Luminex beads. The invention thus relates to an arrangement comprising one or more markers according to the invention, a protein array comprising one or more markers according to the invention, a bead (small ball or platelet) comprising one or more markers according to the invention. Examples of SLE panels (SLE arrangements) are given in Table 4.

The invention also relates to a diagnostic device or a test kit comprising at least one marker for SLE selected from the sequences SEQ ID No. 1 to 1584, homologues of sequences SEQ ID No. 1 to 1584 with at least 95% homology, subsequences of SEQ ID No. 1 to 1584 and subsequences of homologues of SEQ ID No. 1 to 1584 with at least 95% homology, and the proteins coded by the sequences. A corresponding diagnostic device or a corresponding test kit can also comprise a panel of markers for SLE and optionally further auxiliaries and additives.

The invention also relates to the use of one or more markers for SLE selected from sequences SEQ ID No. 1 to 1584, homologues of sequences SEQ ID No. 1 to 1584 with at least 95% homology, subsequences of SEQ ID No. 1 to 1584 and subsequences of homologues of SEQ ID No. 1 to 1584 with at least 95% homology, and the proteins coded by the sequences, a marker panel for SLE, or a diagnostic device or test kit for identifying subgroups of SLE patients, for diagnosing SLE, for differential diagnosis (i.e. for distinction from other autoimmune diseases or other rheumatic diseases), for prognosis in the case of SLE, for therapy control in the case of SLE, for active substance selection in the case of SLE, for therapy monitoring in the case of SLE, or for aftercare in the case of SLE.

The invention also relates to the use of one or more of the markers for SLE selected from the sequences SEQ ID No. 1 to 1584, homologues of sequences SEQ ID No. 1 to 1584 with at least 95% homology, subsequences of SEQ ID No. 1 to 1584 and subsequences of homologues of SEQ ID No. 1 to 1584 with at least 95% homology, and the proteins coded by the sequences for the differentiation of SLE from RA and/or other autoimmune diseases, for example SSc and/or SPA and/or RA and/or early RA.

The invention also relates to the use of one or more markers for SLE selected from the sequences SEQ ID No. 112 to 213 and 278, SEQ ID No. 639 to 741 and 806 and SEQ ID No. 1168 to 1270 and 1335, homologues of SEQ ID No. 112 to 213 and 278, SEQ ID No. 639 to 741 and 806 and SEQ ID No. 1168 to 1270 and 1335 with at least 95% homology, subsequences of SEQ ID No. 112 to 213 and 278, SEQ ID No. 639 to 741 and 806 and SEQ ID No. 1168 to 1270 and 1335 and subsequences of homologues of SEQ ID No. 112 to 213 and 278, SEQ ID No. 639 to 741 and 806 and SEQ ID No. 1168 to 1270 and 1335 with at least 95% homology, and the proteins coded by the sequences for the diagnosis of SLE in ENA-4-negative SLE patients.

The invention also relates to the use of one or more markers for SLE selected from the sequences SEQ ID No. 25 to 54, SEQ ID No. 552 to 581 and SEQ ID No. 1081 to 1110, homologues of SEQ ID No. 25 to 54, SEQ ID No. 552 to 581 and SEQ ID No. 1081 to 1110 with at least 95% homology, subsequences of SEQ ID No. 25 to 54, SEQ ID No. 552 to 581 and SEQ ID No. 1081 to 1110 and subsequences of homologues of SEQ ID No. 25 to 54, SEQ ID No. 552 to 581 and SEQ ID No. 1081 to 1110 with at least 95% homology, and the proteins coded by the sequences for the diagnosis and differential diagnosis of lupus nephritis in SLE patients. Lupus nephritis is a common and serious complication of SLE. In the case of complete failure of the kidney function, therapy with dialysis is necessary. In order to avoid long-term damage, it is therefore important to identify and treat any kidney involvement early on. This is also of particular importance for the development of active substances for SLE in general, i.e. for the development of active substances for patients with lupus nephritis. Previously, there were still no biomarkers available able to diagnose lupus nephritis in all patients.

The invention also relates to markers for SLE and lupus nephritis selected from the sequences SEQ ID No. 25 to 54, SEQ ID No. 552 to 581 and SEQ ID No. 1081 to 1110, homologues of SEQ ID No. 25 to 54, SEQ ID No. 552 to 581 and SEQ ID No. 1081 to 1110 with at least 95% homology, subsequences of SEQ ID No. 25 to 54, SEQ ID No. 552 to 581 and SEQ ID No. 1081 to 1110 and subsequences of homologues of SEQ ID No. 25 to 54, SEQ ID No. 552 to 581 and SEQ ID No. 1081 to 1110 with at least 95% homology, and the proteins coded by the sequences.

The autoantibody profiles of SLE patients with lupus nephritis were therefore compared with those without lupus nephritis. Following univariate statistical evaluation, a threshold value of p<0.05 and a 1.5 times modified reactivity compared with the control group were applied.

The invention also relates to a method for the early detection, diagnosis, differential diagnosis, prognosis, therapy control and/or after-care of SLE, in which

  • a. at least one of the markers for SLE selected from the sequences SEQ ID No. 1 to 1584, the homologues of sequences SEQ ID No. 1 to 1584 with at least 95% homology, the subsequences of SEQ ID No. 1 to 1584 or the subsequences of homologues of SEQ ID No. 1 to 1584 with at least 95% homology, and the proteins coded by the sequences
  • b. is brought into contact with bodily fluid or a tissue sample from an individual to be tested, and
  • c. an interaction of the bodily fluid or of the tissue sample with the one this or more markers from a. is detected.

The invention also relates to a target for the therapy of SLE selected from the sequences SEQ ID No. 1 to 1584, the homologues of sequences SEQ ID No. 1 to 1584 with at least 95% homology, the subsequences of SEQ ID No. 1 to 1584 and the subsequences of homologues of SEQ ID No. 1 to 1584 with at least 95% homology, and the proteins coded by the sequences.

The invention also relates to a composition, in particular a pharmaceutical composition, comprising at least one of the sequences SEQ ID No. 1 to 1584, the homologues of sequences SEQ ID No. 1 to 1584 with at least 95% homology, the subsequences of SEQ ID No. 1 to 1584 or the subsequences of the homologues of SEQ ID No. 1 to 1584 with at least 95% homology, and the proteins coded by the sequences.

The invention also relates to a method for screening active substances for SLE, in which

  • a. at least one of the markers for SLE selected from the sequences SEQ ID No. 1 to 1584, the homologues of sequences SEQ ID No. 1 to 1584 with at least 95% homology, the subsequences of SEQ ID No. 1 to 1584 or the subsequences of homologues of SEQ ID No. 1 to 1584 with at least 95% homology, and the proteins coded by the sequences
  • b. is brought into contact with a substance to be tested, and
  • c. an interaction of the substance with the one or more markers from a. is detected.

The large clinical heterogeneity of SLE currently constitutes a big problem both for diagnosis and for active substance development.

The identification of specific antibody signatures in SLE patient subgroups therefore constitutes an important step for the improved definition of patient groups in clinical studies.

By way of example, as presented under Example 9, specific autoantibodies for lupus nephritis could be used to recruit this subgroup for drug studies.

A large number of new active substances and therapeutic antibodies are currently undergoing clinical development: inter alia, therapeutic antibodies against cell-surface receptors of immune cells, such as anti-CD20, anti-CD22, or against pro-inflammatory cytokines, such as anti-IL6, are being developed. It is therefore now possible, due to the identification of serologically defined subgroups of SLE, to link this to a target-specific response to a drug. The invention also relates to the use of one or more markers for SLE according to the invention, of an arrangement according to the invention (panel of markers for SLE), of a protein array according to the invention, of a bead according to the invention, of a diagnostic device according to the invention, or of a test kit according to the invention for the individualised diagnosis and/or therapy in individual patients, patient groups, cohorts, population groups, variants of SLE, or stages of SLE.

The invention also relates to the use of one or more markers according to the invention for SLE, of an arrangement according to the invention (panel of markers for SLE), of a protein array according to the invention, of a bead according to the invention, of a diagnostic device according to the invention, or of a test kit according to the invention for the detection and/or determination of the amount of one or more autoantibodies associated with SLE, for example in bodily fluids such as serum, tissue or tissue samples of the patient. The invention also relates to the use of one or more markers according to the invention, of an arrangement according to the invention, of a protein array according to the invention, of a bead according to the invention, of a diagnostic device according to the invention, or of a test kit according to the invention for the analysis of autoantibody profiles of patients, in particular for the qualitative and/or quantitative analysis of autoantibodies and/or for the monitoring of changes of autoantibody profiles associated with SLE, for example in bodily fluids such as serum, tissue or tissue samples of the patient.

A particular embodiment of the invention relates to methods for the early identification and diagnosis of SLE, in which the detection of an interaction of the bodily fluid or the tissue sample with the one or more markers indicates an SLE-associated autoantibody profile of the patient or of a cohort or of a population group or of a certain course of disease (prognosis) or of a certain response to a therapy/drug. The invention therefore includes the use of at least one marker for SLE selected from the sequences SEQ ID No. 1 to 1584, the homologues of sequences SEQ ID No. 1 to 1584 with at least 95% homology, the subsequences of SEQ ID No. 1 to 1584 or the subsequences of homologues of SEQ ID No. 1 to 1584 with at least 95% homology, and the proteins coded by the sequences for the analysis of autoantibody profiles of patients, in particular for the quantitative analysis and/or for the monitoring of changes of autoantibody profiles of SLE patients.

An interaction of the bodily fluid or the tissue sample with the one or more SLE markers can be detected for example by a probe, in particular by an antibody.

In a preferred embodiment at least 2, for example 3, 4, 5, 6, 7, 8, 9, 10, preferably 15 to 20 markers for SLE or 30 to 50 or 100 or more markers are used together or in combination, either simultaneously or in succession, wherein the markers for SLE are selected independently of one another from the sequences SEQ ID No. 1 to 1584, the homologues of sequences SEQ ID No. 1 to 1584 with at least 95% homology, the subsequences of SEQ ID No. 1 to 1584 or the subsequences of homologues of SEQ ID No. 1 to 1584 with at least 95% homology, and the proteins coded by the sequences.

A particular embodiment of the invention relates to a method according to the invention, wherein the stratification or therapy control includes decisions relating to the treatment and therapy of the patient, in particular hospitalisation of the patient, use, efficacy and/or dosage of one or more drugs, a therapeutic measure, or the monitoring of the course of the disease and course of therapy, aetiology, or classification of a disease inclusive of prognosis. The invention also relates to a method for stratification, in particular for risk stratification and/or therapy control of a patient with SLE.

The stratification of the patient with SLE into new or established SLE subgroups as well as the expedient selection of patient groups for the clinical development of new therapeutic agents is also included. The term therapy control likewise includes the division of patients into responders and non-responders with regard to a therapy or course thereof.

The invention in particular also relates to the detection and determination of the amount of at least two different autoantibodies in a patient by means of the SLE markers according to the invention, wherein at least two different SLE markers are preferably used. The invention also relates to a use according to the invention of one or more SLE markers, wherein at least 2, for example 3 to 5 or 10, preferably 30 to 50, or 50 to 100 or more SLE markers or the relevant autoantibodies on or from a patient to be tested are determined.

The invention comprises the SLE markers on a solid substrate, for example a filter, a membrane, a small platelet or ball, for example a magnetic or fluorophore-labelled ball, a silicon wafer, a bead, a chip, a mass spectrometry target, or a matrix, or the like. Different materials are suitable as substrates and are known to a person skilled in the art, for example glass, metal, plastic, filter, PVDF, nitrocellulose, or nylon (for example Immobilon P Millipore, Protran Whatman, Hybond N+ Amersham).

The substrate for example can correspond to a grid with the dimensions of a microtitre plate (8-12 well strips, 96 wells, 384 wells or more), of a silicon wafer, of a chip, of a mass spectrometry target, or of a matrix.

In one embodiment of the invention markers for SLE are present in the form of clone sequences or clone(s).

The markers according to the invention can be combined, supplemented or extended with known biomarkers for SLE or biomarkers for other diseases. With a combination of this type, a proportion of markers for SLE according to the invention of preferably at least 50%, preferably 60%, and particularly preferably 70% or more is comprised.

In a preferred embodiment the use of the SLE markers and the methods according to the invention are implemented outside the human or animal body, for example the diagnosis is performed ex vivo/in vitro, preferably by means of an assay, as detailed below.

In the sense of this invention, the term “diagnosis” means the positive determination of SLE with the aid of the markers according to the invention and the assignment of the patients or symptoms thereof to the disease SLE. The term “diagnosis” includes the medical diagnosis and tests in this respect, in particular in vitro diagnosis and laboratory diagnosis, and also proteomics and nucleic acid blots. Further tests may be necessary for assurance and in order to rule out other diseases. The term “diagnosis” therefore includes in particular the differential diagnosis of SLE by means of the markers according to the invention.

In the sense of this invention, “stratification or therapy control” means that, for example, the methods according to the invention allow decisions for the treatment and therapy of the patient, whether it is the hospitalisation of the patient, the use, efficacy and/or dosage of one or more drugs, a therapeutic measure or the monitoring of the course of a disease and the course of therapy or aetiology or classification of a disease, for example into a new or existing sub-type, or the differentiation of diseases and patients thereof. In a further embodiment of the invention, the term “stratification” in particular includes the risk stratification with the prognosis of an “outcome” of a negative health event.

“Prognosis” means the prediction of the course of a disease.

In accordance with the invention, “therapy control” means, for example, the prediction and monitoring of the response to a drug or a therapy as well as aftercare.

Within the scope of this invention, the term “patient” is understood to mean any test subject, any individual (human or mammal), with the provision that the test subject or individual is tested for SLE.

The term “marker for SLE” in the sense of this invention means that the nucleic acid, for example DNA, in particular cDNA or RNA or the coded amino acid sequence or the polypeptide or protein are significant (specific) for SLE and/or the autoantibody profiles associated with SLE. Markers according to the invention are nucleic acid sequences and/or amino acid sequences according to the definition in the appended sequence protocol (SEQ ID No. 1 to SEQ ID No. 1584), homologues and subsequences thereof, wherein modified nucleic acid and amino acid sequences are also included. Here, marker for SLE means, for example, that the cDNA or RNA or the polypeptide or protein obtainable therefrom interacts with substances from the bodily fluid or tissue sample from a patient with SLE (for example antigen (epitope)/antibody (paratope) interaction). In a particularly preferred embodiment of the invention the marker for SLE is an antigen or part of an antigen or codes for an antigen or for part of an antigen.

The substances from the bodily fluid or tissue sample occur either only in an amplified manner or at least in an amplified manner in the case of SLE or are expressed, whereas these substances are not present in patients without SLE or healthy individuals, or at least are present to a lesser extent (smaller amount, lower concentration). Markers for SLE can also be characterised in that they interact with substances from the bodily fluid or tissue sample from patients with SLE, because these substances no longer occur or are no longer expressed or occur or are expressed at least in a much lower amount/concentration in the case of SLE, whereas these substances are present or are at least present to a much higher extent in patients without SLE. Markers for SLE can also be present in healthy test subjects, however the amount (concentration) thereof changes for example with the development, establishment and therapy of SLE. One or more markers can in this way map a profile of substances from bodily fluid and tissue sample, for example an SLE-associated autoantibody profile of the patient in question. Markers according to the invention are biomarkers for SLE.

Autoantibody profiles comprise the amount of one or more autoantibodies of which the occurrence/expression accompanies the development and/or establishment of SLE. Autoantibody profiles therefore include on the one hand the composition, i.e. one or more autoantibodies is/are expressed only in the case of SLE for example, and also the amount/concentration of individual autoantibodies, i.e. the amount/concentration of individual autoantibodies changes with the development and establishment of SLE. These changes can be detected with the aid of the marker sequences according to the invention.

In a particularly preferred embodiment the SLE marker identifies/binds to autoantibodies which are present (intensified) or are present to a lower extent (or no longer) during the course of the development, establishment and therapy of SLE. Autoantibodies are formed by the body against endogenous antigens which are formed for example in the case of SLE. Autoantibodies are formed by the body against different substances and pathogens. Within the scope of the present invention, the autoantibodies which are formed with the occurrence and during the course of the development of SLE and/or of which the expression is up-regulated or down-regulated are detected in particular. These autoantibodies can be detected with the aid of the methods and markers according to the invention, and the detection and monitoring (for example of the amount) thereof can be used for the early identification, diagnosis and/or therapy monitoring/therapy control and the prognosis and prediction of the risk of the re-occurrence of SLE within the scope of the after-care.

The autoantibody profiles can be sufficiently characterised with use of just a single SLE marker. In other cases, two or more SLE markers are necessary in order to map an autoantibody profile which is specific for SLE.

In one embodiment of the invention autoantibodies which derive from another individual and which for example originate from a commercial cDNA bank can be detected using SLE markers.

In another embodiment of the invention these autoantibodies can be detected using SLE markers which derive from the same individual and which for example originate from a cDNA bank produced individually for the patient or a group of patients for example within the scope of individualised medicine. By way of example, homologues of the specified SLE markers with the sequences SEQ ID. No. 1 to 1584 or subsequences thereof can be used.

Autoantibodies can be formed by the patient already many years prior to the occurrence of the first symptoms of disease. An early identification, diagnosis and also prognosis and preventative treatment or lifestyle change and other possibilities for prevention might therefore be possible even years prior to the visible outbreak of the disease. The devices, means and methods according to the invention enable a very early intervention compared with known methods, which significantly improves the prevention, treatment possibilities and effects of SLE.

Since the SLE-associated autoantibody profiles change during the establishment and treatment/therapy of SLE, the invention also enables the detection and monitoring of SLE at any stage of the development and treatment and also monitoring within the scope of SLE after-care. The means according to the invention, for example a corresponding diagnostic device or a test kit, also allow simple handling at home by the patient and an economical routine precautionary measure for early identification.

In particular due to the use of antigens as specific markers for SLE which derive from sequences already known, for example from commercial cDNA banks, test subjects can be tested and any present SLE-associated autoantibodies can be detected in these test subjects, even if the corresponding autoantigens are not (yet) known in these test subjects.

Different patients can have different SLE-associated autoantibody profiles, for example different cohorts or population groups can differ from one another. Here, any patient can form one or more different SLE-associated autoantibodies during the course of the development of SLE and the progression of the SLE disease, that is to say even different autoantibody profiles. In addition, the composition and/or the amount of formed autoantibodies can change during the course of the SLE development and progression of the disease, such that a quantitative evaluation is necessary. The therapy/treatment of SLE leads to changes in the composition and/or the amount of SLE-associated autoantibodies. The large selection of SLE markers according to the invention which are provided with this invention enables the individual compilation of SLE markers in an arrangement, i.e. a panel, for individual patients, groups of patients, certain cohorts, population groups and the like. In one individual case, the use of one SLE marker may therefore be sufficient, whereas in other cases at least two or more SLE markers must be used together or in combination in order to create a conclusive autoantibody profile.

Compared with other biomarkers, the detection of SLE-associated autoantibodies for example in the serum or plasma of patients has the advantage of high stability and storage capability and good detectability. The presence of autoantibodies also is not subject to a circadian rhythm, and therefore the sampling is independent of the time of day, food intake, and the like.

In addition, the SLE-associated autoantibodies can be detected with the aid of the corresponding antigens/autoantigens in known assays, such as ELISA or Western Blot, and the results can be checked in this way.

In the sense of the invention, an interaction between the SLE marker and the serum in question, for example an autoantibody of the patient, is detected. Such an interaction is, for example, a bond, in particular a binding substance on at least one SLE-specific marker, or, in the case that the SLE-specific marker is a nucleic acid, for example a cDNA, the hybridisation with a suitable substance under selected conditions, in particular stringent conditions (for example as defined conventionally in J. Sambrook, E. F. Fritsch, T. Maniatis (1989), Molecular cloning: A laboratory manual, 2nd Edition, Cold Spring Harbor Laboratory Press, Cold Spring Harbor, USA or Ausubel, “Current Protocols in Molecular Biology”, Green Publishing Associates and Wiley Interscience, N.Y. (1989)). One example of stringent hybridisation conditions is: hybridisation in 4×SSC at 65° C. (alternatively in 50% formamide and 4×SSC at 42° C.), followed by a number of washing steps in 0.1×SSC at 65° C. for a total of approximately one hour. An example of less stringent hybridisation conditions is hybridisation in 4×SSC at 37° C., followed by a number of washing steps in 1×SSC at room temperature. The interaction between the bodily fluid or tissue sample from a patient and the markers for SLE is preferably a protein-protein interaction.

In accordance with the invention, such substances, for example antigens, autoantigens and SLE-associated autoantibodies, are part of a bodily fluid, in particular blood, whole blood, blood plasma, blood serum, patient serum, urine, cerebrospinal fluid, synovial fluid or a tissue sample from the patient. The invention in particular relates to the use of these bodily fluids and tissue samples for early detection, diagnosis, prognosis, therapy control and aftercare.

The SLE-specific markers, in a further embodiment of the invention, have a recognition signal that is addressed to the substance to be bound (for example antibody, nucleic acid). In accordance with the invention, the recognition signal for a protein is preferably an epitope and/or paratope and/or hapten, and for a cDNA is preferably a hybridisation or binding region.

Homologues of the markers according to the invention SEQ ID No. 1 to 1584, as presented in the claims for example are also included. Within the sense of the invention, homologues are those with homology of the amino or nucleic acid sequence and those in which the corresponding sequence is modified, for example the protein variants, which indeed have the same amino acid sequence, but differ with regard to the modification, in particular the post-translational modification.

In accordance with the invention, modifications of the nucleic acid sequence and of the amino acid sequence, for example citrullination, acetylation, phosphorylation, glycosylation, ethylation, or polyA strand extensions and further modifications known as appropriate to a person skilled in the art are included.

Homologues also include sequence homologues of the markers and subsequences thereof. Sequence homologues are, for example, nucleic acid sequences and/or protein sequences that have an identity with the SLE markers of the sequences SEQ ID No. 1 to 1584 of at least 70% or 80%, preferably 90% or 95%, particularly preferably 96% or 97% or more, for example 98% or 99%. In a particularly preferred embodiment of the invention, for the case in which the SLE markers are antigens, the homology in the sequence range in which the antigen-antibody or antigen-autoantibody interaction takes place, is at least 95%, preferably at least 97%, particularly preferably at least 99%. For example, mutations such as base exchange mutations, frameshift mutations, base insertion mutations, base loss mutations, point mutations and insertion mutations, are included in accordance with the invention.

The invention also relates to subsequences of the SLE markers with the sequence SEQ ID No. 1 to 1584. Subsequences also include nucleic acid or amino acid sequences that are shortened compared with the entire nucleic acid or the entire protein/peptide. Here, the deletion may occur at the end or the ends and/or within the sequence. For example, subsequences and/or fragments that have 50 to 100 nucleotides or 70-120 nucleotides of the sequence SEQ ID No. 1 to 1584 are included. Homologues of subsequences are also included in accordance with the invention. In a particular embodiment, the SLE markers are shortened compared with the sequences SEQ ID No. 1 to 1584 to such an extent that they still consist only of the binding point(s) for the SLE-associated autoantibody in question. In accordance with the invention, SLE markers are also included that differ from the sequences SEQ ID No. 1 to 1584 in that they contain one or more insertions, wherein the insertions for example are 1 to 100 or more nucleotide/amino acids long, preferably 5 to 50, particularly preferably 10 to 20 nucleotides/amino acids long and the sequences are otherwise identical however or homologous to sequences SEQ ID No. 1 to 1584. Subsequences that have at least 90%, preferably at least 95%, particularly preferably 97% or 98%, of the length of the SLE markers according to the invention with sequences SEQ ID No. 1 to 1584 are particularly preferred.

In a further embodiment, the respective SLE marker can be represented in different quantities in one or more regions in the arrangement or on the substrate or in a panel. This allows a variation of the sensitivity. The regions may each have a totality of SLE markers, that is to say a sufficient number of different SLE markers, in particular 2, 3, 4, 5, 6, 7, 8, 9 or 10 or more different SLE markers. By way of example, 20 to 50 (numerically) or more, preferably more than 100, particularly preferably 150 or more, for example 25,000 or 5000 or 10000 different or same SLE marker sequences and where applicable further nucleic acids and/or proteins, in particular other biomarkers can be represented on the substrate or in the panel.

One or more panels as presented in the examples and selected from the sequences, preferably protein sequences, consisting of at least two markers, five markers or 10 markers or more, selected from:

panel I (P1)

SEQ ID No. 1, 2, 3, 5, 7, 8, 10, 12, 13, 15, 17, 18, 19, 20, 24,

SEQ ID No. 528, 529, 530, 532, 534, 535, 537, 539, 540, 542, 544, 545, 546, 547, 551, preferably

SEQ ID No. 1057, 1058, 1059, 1061, 1063, 1064, 1066, 1068, 1069, 1071, 1073, 1074, 1075, 1076, 1080, and/or

panel II (P2)

SEQ ID No. 1, 3, 4, 5, 7, 12, 13, 14, 15, 17, 18, 19, 20, 24

SEQ ID No. 528, 530, 531, 532, 534, 539, 540, 541, 542, 544, 545, 546, 547, 551, preferably

SEQ ID No. 1057, 1059, 1060, 1061, 1063, 1068, 1069, 1070, 1071, 1073, 1074, 1075, 1076, 1080, and/or

panel III (P3)

SEQ ID No. 1, 2, 3, 5, 6, 7, 8, 9, 10, 15, 16, 18, 21, 23

SEQ ID No. 528, 529, 530, 532, 533, 534, 535, 536, 537, 542, 543, 545, 548, 550, preferably

SEQ ID No. 1057, 1058, 1059, 1061, 1062, 1063, 1064, 1065, 1066, 1071, 1072, 1074, 1077, 1079, and/or

panel IV (P4)

SEQ ID No. 1, 2, 3, 4, 5, 8, 9, 10, 12, 13, 14, 15, 17, 19, 20

SEQ ID No. 528, 529, 530, 531, 532, 533, 536, 537, 539, 540, 541, 542, 544, 546, 547, preferably

SEQ ID No. 1057, 1058, 1059, 1060, 1061, 1064, 1065, 1066, 1068, 1069, 1070, 1071, 1073, 1075, 1076, and/or

panel V

SEQ ID No. 1, 2, 3, 4, 5, 6, 7, 11, 15, 16, 18, 21, 22, 23, 24

SEQ ID No. 528, 529, 530, 531, 532, 533, 534, 538, 542, 543, 545, 548, 549, 550, 551, preferably

SEQ ID No. 1057, 1058, 1059, 1060, 1061, 1062, 1063, 1067, 1071, 1072, 1074, 1077, 1078, 1079, 1080, and/or

panel VI

SEQ ID No. 2, 5, 6, 7, 8, 10, 13, 18, 19, 22, 168

SEQ ID No. 529, 532, 533, 534, 535, 537, 540, 545, 546, 549, 695, preferably

SEQ ID No. 1058, 1061, 1062, 1063, 1064, 1066, 1069, 1074, 1075, 1078, 1224, and/or

panel VII

SEQ ID No. 1, 2, 5, 6, 7, 8, 9, 10, 13, 15, 19, 22, 24, 134, 168, 213, 367, 368, 369

SEQ ID No. 528, 529, 532, 533, 534, 535, 536, 537, 540, 542, 546, 549, 551, 661, 695, 741, 895, 896, 897, preferably

SEQ ID No. 1057, 1058, 1061, 10642, 1063, 1064, 1065, 1066, 1069, 1071, 1075, 1078, 1080, 1190, 1224, 1270, 1424, 1425, 1426, and/or

panel VIII (P8)

SEQ ID No. 1, 2, 4, 5, 6, 7, 8, 9, 10, 12, 13, 15, 17, 18, 19, 20, 21, 22, 23, 24, 29, 31, 46, 95, 128, 134, 136, 143, 163, 168, 169, 171, 188, 213, 348, 367, 368, 369, 370-391, 423-433

SEQ ID No. 528, 529, 531, 532, 533, 534, 535, 536, 537, 539, 540, 542, 544, 545, 546, 547, 548, 549, 550, 551, 556, 558, 573, 622, 655, 661, 663, 690, 695, 696, 698, 715, 741, 876, 895, 896, 897, 898-919, 951-961, preferably

SEQ ID No. 1057, 1058, 1060, 1061, 1062, 1063, 1064, 1065, 1066, 1068, 1069, 1071, 1073, 1074, 1075, 1076, 1077, 1078, 1079, 1080, 1085, 1087, 1102, 1151, 1184, 1190, 1192, 1219, 1220, 1224, 1225, 1227, 1244, 1270, 1405, 1424, 1425, 1426, 1427-1448, 1480-1490, and/or

panel IX (P9)

SEQ ID No. 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 29, 31, 33, 41, 46, 48, 74, 95, 105, 108, 114, 115, 116, 128, 132, 134, 136, 143, 163, 168, 169, 171, 188, 213, 348, 367, 368, 369, 370-391, 423-433

SEQ ID No. 528, 529, 530, 531, 532, 533, 534, 535, 536, 537, 538, 539, 540, 541, 542, 543, 544, 545, 546, 547, 548, 549, 550, 551, 556, 558, 560, 568, 573, 575, 601, 622, 632, 635, 641, 642, 643, 655, 659, 661, 663, 670, 690, 695, 696, 698, 715, 741, 876, 895, 896, 897, 898-919, 951-961, preferably

SEQ ID No. 1057, 1058, 1059, 1060, 1061, 1062, 1063, 1064, 1065, 1066, 1067, 1068, 1069, 1070, 1071, 1072, 1073, 1074, 1075, 1076, 1077, 1078, 1079, 1080, 1085, 1087, 1089, 1097, 1102, 1104, 1130, 1151, 1161, 1164, 1170, 1171, 1172, 1184, 1188, 1190, 1192, 1199, 1219, 1224, 1225, 1227, 1244, 1270, 1405, 1424, 1425, 1426, 1427-1448, 1480-1490

or respective homologues or subsequences thereof, as mentioned previously with regard to the individual marker sequences, is/are very particularly preferred.

These aforementioned panels particularly advantageously allow the execution of the method according to the invention; see the examples.

Within the scope of this invention, “arrangement” is synonymous with “array”, and, if this “array” is used to identify substances on SLE markers, this is to be understood preferably to be an “assay” or a bead or a diagnostic device or a screening assay. In a preferred embodiment, the arrangement is designed such that the markers represented on the arrangement are present in the form of a grid on a substrate. Furthermore, those arrangements are preferred that permit a high-density arrangement of SLE markers. The markers are preferably spotted. Such high-density spotted arrangements are disclosed for example in WO 99/57311 and WO 99/57312 and can be used advantageously in a robot-supported automated high-throughput method.

Within the scope of this invention, however, the term “assay” or diagnostic device likewise comprises those embodiments such as ELISA, bead-based assay, line assay, Western Blot, and immunochromatographic methods (for example what are known as lateral flow immunoassays) or similar immunological single or multiplex detection methods.

A “protein array” in the sense of this invention is the systematic arrangement of SLE markers on a solid substrate, wherein the substrate can have any shape and/or size, and wherein the substrate is preferably a solid substrate.

The SLE markers of the arrangement/panel are fixed on the substrate, preferably spotted or immobilised, printed on or the like, in particular in a reproducible manner. One or more SLE markers can be present multiple times in the totality of all SLE markers and may be present in different quantities based on a spot. Furthermore, the SLE markers can be standardised on the substrate (for example by means of serial dilution series of, for example, human globulins as internal calibrators for data normalisation and quantitative evaluation). A standard (for example a gold standard) can also be applied to the substrate where necessary.

In a further embodiment, the SLE markers are present as clones. Such clones can be obtained for example by means of a cDNA expression library according to the invention. In a preferred embodiment, such expression libraries are obtained using expression vectors from a cDNA expression library comprising the cDNAs of the SLE-specific marker sequences. These expression vectors preferably contain inducible promoters. The induction of the expression can be carried out for example by means of an inducer, such as IPTG. Suitable expression vectors are described in Terpe et al. (Terpe T Appl Microbiol Biotechnol. 2003 January; 60(5):523-33).

Expression libraries are known to a person skilled in the art; they can be produced in accordance with standard works, such as Sambrook et al, “Molecular Cloning, A laboratory handbook, 2nd edition (1989), CSH press, Cold Spring Harbor, N.Y. Expression libraries that are tissue-specific (for example human tissue, in particular human organs) are furthermore preferable. Further, expression libraries that can be obtained by means of exon trapping are also included in accordance with the invention.

Protein arrays or corresponding expression libraries that do not exhibit any redundancy (what is known as a Uniclone® library) and that can be produced for example in accordance with the teaching of WO 99/57311 and WO 99/57312 are furthermore preferred. These preferred Uniclone® libraries have a high proportion of non-defective fully expressed proteins of a cDNA expression library.

Within the scope of this invention, the clones can also be, but are not limited to, transformed bacteria, recombinant phages or transformed cells of mammals, insects, fungi, yeasts or plants.

The clones are fixed, spotted or immobilised on a solid substrate. The invention therefore relates to an arrangement/use, wherein the SLE-specific markers are present as clones.

In addition, the SLE markers can be present in the respective form in the form of a fusion protein, which for example contains at least one affinity epitope or “tag”, wherein the tag is selected for example from c-myc, his tag, arg tag, FLAG, alkaline phosphatase, V5 tag, T7 tag or strep tag, HAT tag, NusA, S tag, SBP tag, thioredoxin, DsbA, or the fusion protein has one or more additional domains for example, such as a cellulose-binding domain, green fluorescent protein, maltose-binding protein, calmodulin-binding protein, glutathione S-transferase or lacZ.

In a further embodiment the invention relates to an assay, for example a multiplex assay, a bead-based assay, or protein array for identifying and characterising a substance, for example a hit, a lead substance, or an active substance for SLE. Here, a substance to be tested is used. This can be any native or non-native biomolecule, a (synthetic) chemical molecule, a natural substance, a mixture or a substance library. Once the substance to be tested has contacted an SLE marker, the binding success is evaluated, for example with use of commercially available image-analysis software (GenePix Pro (Axon Laboratories), Aida (Raytest), ScanArray (Packard Bioscience).

Binding according to the invention, binding success, interactions, for example protein-protein interactions (for example protein to SLE marker, such as antigen/antibody) or corresponding “means for detecting the binding success” can be visualised for example by means of fluorescence labelling, biotinylation, radio-isotope labelling or colloid gold or latex particle labelling in the conventional manner. Bound antibodies are detected with the aid of secondary antibodies, which are labelled using commercially available reporter molecules (for example Cy, Alexa, Dyomics, FITC or similar fluorescent dyes, colloidal gold or latex particles), or with reporter enzymes, such as alkaline phosphatase, horseradish peroxidase, etc. and the corresponding colorimetric, fluorescent or chemoluminescent substrates. A readout is performed for example by means of a microarray laser scanner, a CCD camera or visually.

In a further embodiment, the invention relates to a drug or an active substance or prodrug for SLE, developed and obtainable by the use of an SLE marker according to the invention.

The invention also relates to the use of an SLE marker selected from sequences SEQ ID No. 1 to 1584 and subsequences of SEQ ID No. 1 to 1584 with at least 90%, preferably at least 95% of the length of SEQ ID No. 1 to 1584 and homologues of SEQ ID No. 1 to 1584 and subsequences thereof with an identity of at least 95%, preferably at least 98% or more, to the corresponding sequences and proteins/peptides coded by the sequences SEQ ID No. 1 to 1056, coded by the subsequences thereof and homologues as affinity material for carrying out an apheresis or blood washing for patients with SLE, i.e. apheresis of SLE autoantibodies. The invention thus relates to the use of the markers according to the invention, preferably in the form of an arrangement, as affinity material for carrying out an apheresis or a blood washing in the broader sense, wherein substances from bodily fluids from a patient with SLE, such as blood or plasma, bind to the markers according to the invention and consequently can be removed selectively from the bodily fluid. The application in blood washing is a special case of use of the SLE markers as a target. Devices for carrying out a blood washing, in particular immunapheresis, are known to a person skilled in the art and can be carried out for example by means of dialysis.

The following examples and drawings explain the invention, but do not limit the invention to the examples.

FIG. 1 shows a volcano plot of the relative antigen reactivities of the SLE patients compared to healthy controls.

FIG. 2 shows a volcano plot of the relative antigen reactivities of the SLE patients compared to RA patients.

FIG. 3: volcano plot of the antigen reactivities of SLE patients compared with a combined group of patients with various autoimmune diseases, such as SSc (PSS), SPA, early rheumatoid arthritis and SPA.

FIG. 4 frequency of the autoantibody reactivities of selected antigens in SLE patients and healthy test subjects. A threshold value of 3 SD deviations above the mean value of the healthy test subject was applied. The threshold value for the antigen SNRNP was set to 2SD.

FIG. 5: volcano plot of the autoantibody reactivities of ENA-4-negative SLE patients compared with healthy controls.

FIG. 6: receiver operating characteristic curves (ROCs) for the diagnosis of SLE compared to healthy test subjects and AID samples

FIG. 7: volcano plot for SLE lupus nephritis compared with SLE without lupus nephritis

FIG. 8: frequency of the lupus nephritis antigens in a model with nested cross validation.

FIG. 9: dendogram of the SLE antigens following calculation of Spearman's rank correlation coefficient a) dendogram of the known ENA-4 antigens and b) dendogram of 50 selected SLE antigens.

FIG. 10: PPLS-DA biplot of the SLE patients and healthy controls with use of the SLE antigens a) PPLS-DA biplot based on the ENA-4 and ribosomal antigen b) PPLS-DA biplot based on 50 SLE antigens.

EXAMPLES Example 1 Selection of the SLE Patients and Test Subjects

Selection of the patient groups to be tested: Blood samples were analysed from 129 SLE patients, 100 patients with systemic sclerosis (SSc, PSS), 75 patients with rheumatoid arthritis (RA), 537 patients with early RA (period of disease less than 6 months) and 75 patients with ankylosing spondylitis (SPA)/Bekhterev's disease (SPA). 343 blood samples from the Bavarian Red Cross (BRC) were used as control group. An informed consent of the Ethics Commission of the clinical partners and of the biobank of the BRC was received from all test subjects.

TABLE 1 Patient samples and clinical data (test cohort I) 2. Screen SSc (PSS) 1. Screen Sub- Early RA SLE RA Healthy SLE Total type (<6 months) SPA Healthy Number 129  75 123 100  100  537 82   343 Age 39 +/− 56.6 +/− 41.3 +/− 39.8 +/− 56.9 +/− Lim- 56.8 +/− 43.7 +/− 47.7 +/− (years) 12 13.2 11 11.9 13.4 ited 14.3 10.1 11.7 n = 50 % female   86.1 72   86.2 83 87 Dif-   62.2 15.9   58.3 fuse n = 32 % ANA   77.5 N.D. N.D. 100  95 Over- N.D. N.D. N.D. lap n = 9 SLAM 7.7 +/− 7.7 +/− 5.1 5.1 SLICC 1.45 +/− 1.45 +/− 1.8 1.8 ANA % ENA-4 37 48 positive % U1-RNP 13 13 (% of ENA-4 pos.) Sm  8  8 (% of ENA-4 pos.) SS-A/Ro52 35 35 (% of ENA-4 pos.) SS-B/R060 10 10 (% of ENA-4 pos.) Kidney   26.4 34 involvement %

Example 2 Antigen Production

Five cDNA libraries that had been produced from different human tissues (foetal brain, intestine, lung, liver and T-cells) were used for the production of the recombinant antigens. All cDNAs were expressed in E. coli under the transcriptional control of the lactose-inducible promoter. The resultant proteins carry, at their amino terminus, an additional sequence for a hexahistidine purification tag (His6 tag). Target antigens which were not present in the cDNA library were produced by chemical synthesis (Life Technologies) and cloned into the expression vector pQE30-NST, which already codes an amino-terminal His6 tag.

Following recombinant expression of the proteins, these were isolated in denaturising conditions and purified by means of metal affinity chromatography (IMAC). The proteins were lyophilised and stored at −20° C. until further use (lifesciences.sourcebioscience.com).

Example 3 Production of the BBAs

The production of BBAs was adapted to a microtitre plate format, such that 384 coupling reactions could be assessed in parallel using automated pipette systems (Starlet, Hamilton Robotics, Evo Freedom 150, Tecan). For the use of automated pipette systems, the individual bead regions were transferred into coupling plates (96 well Greiner) and the antigens were transferred into 2D barcode vessels (Thermo Scientific). For each coupling reaction, 0.6 to 2.5 million beads and, depending on the antigen, 1 to 100 μg protein were used.

All washing and pipetting steps of the coupling reaction were carried out in coupling plates which were fixed on magnets.

The beads were washed twice with 100 μl LxAP buffer (100 mM NaH2PO4, pH 6.2) and then received in 120 μl LxAP buffer. For the activation, 15 μl 1-ethyl-3-(3-dimethylaminopropyl)carbodiimide (EDC; 50 mg/ml) and 15 μl N-hydroxysulfosuccinimide (sulfo-NHS; 50 mg/ml) were added by pipette to form a bead suspension, and these suspensions were then incubated for 20 minutes in the shaker (RT, 900 rpm, protected against light). The beads were then washed 3× with 150 μl LxKPT buffer and then the protein solution was added. Following an incubation period of two hours in the shaker (RT, 900 rpm, protected against light), the beads were then washed three times with 150 μl LxKPT buffer. To block free binding points, 100 μl LxCBSP buffer (PBS, 1% BSA, 0.05% ProClin300) were added, and these mixtures were then incubated for 20 min in the shaker (RT, 900 rpm, protected against light). This was followed by incubation over night at 4-8° C. The BBA was produced by the combination of beads coupled to antigens and was stored at 4-8° C., protected against light, until use.

Example 4 Quality Control of the BBAs

In order to check the immobilisation of the proteins at the respective bead regions, a coupling control was carried out. Here, different amounts of beads were used (250, 500 and 750 beads per bead region). For a reaction mixture, 500 beads for example per bead region were diluted in LxCBS buffer (PBS, 1% BSA) and transferred into an assay plate (96 well half area microplate, Greiner).

Before each washing step, the assay plate with the beads was placed for 2 minutes on a magnet and the supernatant was then removed. After three washing steps, the beads were incorporated with 100 μl LxWPT buffer (PBS, 0.05% Tween-20), and 10 μg/ml penta-his antibodies (Qiagen) or LxCBS buffer (PBS, 1% BSA) were added by pipette. Following incubation for 45 minutes in the shaker (RT, 900 rpm, protected against light), the supernatant was removed and the beads were washed in two steps. 5 μg/ml goat anti-mouse IgG-PE (Phycoerythrin) or goat anti-human IgG-PE (Dianova) were then added as secondary antibody to the reaction mixture and incubated for 30 minutes. Following two washing steps, 100 μl of carrier liquid (Luminex) was added to the beads. The fluorescence signal of the beads was detected with the aid of the FlexMAP3D instrument. Here, the bead count on the one hand and the median of the fluorescence intensity (MFI value) on the other hand were measured.

Example 5 Application of BBAs

For application, BBAs were incubated with sera and all IgG-based autoantibodies bonded to antigens were detected with the aid of a secondary antibody. In order to enable a high throughput of measurements, the application of BBAs was adapted to a microtiter plate format so that either an 8-channel (Starlet, Hamilton Robotics) or a 96-channel (Evo Freedom 150, Tecan) automated pipetting system could be used. The sera to be examined were transferred into 2D barcode vessels and then diluted 1:100 with assay buffer (PBS, 0.5% BSA, 10% E. coli lysate, 50% low-cross buffer (Candor Technologies)). In order to neutralise human antibodies directed against E. coli, a pre-incubation of the sera dilutions was performed for 20 min. In this time, 500 beads per bead region were distributed in the assay plate. 50 μl of diluted serum were added to the beads in the coupling plate, and the reaction mixtures were incubated for 18-22 h in the shaker (4-8° C., 900 rpm, protected against light). After three washing steps in each case with 100 μl LxWPT buffer, 5 μg/ml of the detection antibody goat anti-human IgG-PE (Dianova) were added to the reaction mixtures and incubated for 1 h in the shaker (RT, 900 rpm). The beads were then washed three times with 100 μl LxWPT and incorporated in 100 μl carrier liquid (Luminex). The fluorescence signal of the beads was detected with the aid of the FlexMAP3D instrument. Here, the bead count on the one hand and the MFI value (median fluorescence intensity) on the other hand were measured.

Example 6 Biostatistical Analysis

The biostatistical analysis comprised univariate and multivariate methods for describing the statistical properties of individual antigens and of groups of antigens. In order to discover interesting candidates for panels, the key property was a good separation between the groups of samples based on the MFI values. In order to find antigen candidates for panel generation, univariate testing, receiver operating characteristic (ROC) analyses, correlation profiles, powered partial least squares discriminant analysis (PPLS-DA) and random forests were used as methods. Biostatistical analyses were subject to expert assessment in order to define final antigen panels.

Before the statistical analysis, the MFI values were log 2-transformed in order to reduce the skew in the distributions. If more than 20% of the values were missing, antigens were excluded from the analysis. Missing values were replaced by median imputation. A quantile normalisation was carried out under consideration of the reference sera in order to normalise, per BBA set, all measured samples on individual plates.

Besides descriptive standardisation for MFI values, non-parametric tests were also carried out with the aid of the two-sided Mann-Whitney-U test in order to uncover differences in the median values of the groups. The test level for multiple testing was corrected in accordance with the Bonferroni-Holm procedure. In addition, the Benjamin-Hochberg procedure inclusive of the determination of the False Discovery Rate (FDR, q-value) was applied. In addition, fold-change and effect size were determined. In order to assess the classification quality, an ROC analysis was carried out, within the scope of which sensitivity, specificity and the area under the ROC curve (AUC) were calculated, in each case inclusive of the 95% confidence interval on the basis of the bootstrap method. Boxplots and volcano plots were used for graphical representation. A scoring system was implemented on the basis of the univariate results.

By means of the application of a PPLS-DA, it was attempted to maximise the correlation between the component of the response matrix. A linear discriminant analysis with the latent component as predictors was used for the final classification. A random forest was applied, in which binary decision trees are combined. The decision trees were formed on the basis of a number of bootstrap samples of a training sample and by random selection of a subgroup of explaining variables at each node. The number of input variables, which was selected randomly with each division step, was determined as the square root of the total number of variables, and the number of trees in the random forest was set to 1000. A cross validation with 500 times throughput was implemented for both multi-variant approaches.

Example 7 Autoantibodies/Antigen Reactivities Differentiate SLE from Healthy Controls, Rheumatoid Arthritis and Other Autoimmune Diseases

In a first screening the antigen reactivities of 129 SLE patients, 75 RA patients, and 134 healthy controls categorised in accordance with age and sex were differentially tested. For this purpose, the autoantibody reactivities of these blood samples were tested on 5857 antigens coupled to Luminex beads.

In order to identify antigens with which the group of all SLE patients can be distinguished from different control groups consisting of healthy samples and patients with RA, univariate statistical tests were carried out. The result of the statistical test is illustrated as a volcano plot for all 5857 antigens. In the volcano plot, the x-axis shows the relative change of the antigen reactivity in SLE patients compared with healthy controls (FIG. 1) and RA patients (FIG. 2). The y-axis presents the p-value of the statistical tests. FIGS. 1 and 2 show that specific autoantibody reactivities were found which are increased in the group of all SLE and which can distinguish both from healthy donors and from RA patients.

Example 8 Autoantibodies/Antigen Reactivities Differentiate SLE from Healthy Controls, Early Rheumatoid Arthritis and Other Autoimmune Diseases

In a second screening with 6088 antigens, the antigens which differentiate between healthy controls and donors with rheumatoid arthritis were tested on patients with early rheumatoid arthritis, SSc and SPA. This is of importance in particular since patients with collagenoses and mixed collagenoses have an overlapping autoantibody profile and therefore are difficult to diagnose, particularly in the early phase.

FIG. 3 shows a volcano plot of the antigen reactivities of SLE patients against a combined group of patients with various autoimmune diseases, such as SSc, SPA, early rheumatoid arthritis, and SPA.

Following univariate statistical evaluation, a threshold value of p<0.05 and a 1.5 times modified reactivity compared with the control group were applied. A final list of antigen reactivities over both screens was established (Table 2).

In order to analyse the frequency of the newly identified antigens in comparison with known antigens, a threshold value of 3 standard deviations (SD) above the mean value of the healthy samples was defined.

Astonishingly, at least 4 additional antigens were identified of which the frequency in SLE patients lies above 15%. These include TMPO (19%) (SEQ ID No. 18), HNRNPA1 (26%) (SEQ ID No. 5), XRCC5 (15%) (SEQ ID No. 22) and MVP (15%) (SEQ ID No. 7).

FIG. 4 shows the frequency of 23 antigens in comparison to the healthy controls.

Table 2 summarises the identified antigen reactivities and different group comparisons.

TABLE 2 List of all antigen reactivities Statistical Test SEQ Gene Panel SLE ENA-4 neg L. Nephr. SLE vs ID No. GeneID Symbol Gene Name Group SLE L. Nephr. Cluster vs HV vs SLE control 1 1629 DBT dihydrolipoamide 1 x x SLE vs branched chain AID transacylase E2 2 1737 DLAT dihydrolipoamide S- 1 x SLE vs acetyltransferase AID 3 7430 EZR ezrin 1 x x x SLE vs AID 4 3017 HIST1H2BD histone cluster 1, 1 x x SLE vs H2bd AID 5 3178 HNRNPA1 heterogeneous 1 x x SLE vs nuclear AID ribonucleoprotein A1 6 3181 HNRNPA2B1 heterogeneous 1 x x SLE vs nuclear AID ribonucleoprotein A2/B1 7 9961 MVP major vault protein 1 x x x x SLE vs AID 8 6175 RPLP0 ribosomal protein, 1 x x x SLE vs large, P0 AID 9 6176 RPLP1 ribosomal protein, 1 x x x x SLE vs large, P1 AID 10 6181 RPLP2 ribosomal protein, 1 x x x SLE vs large, P2 AID 11 30011 SH3KBP1 SH3-domain kinase 1 x x SLE vs binding protein 1 AID 12 6625 SNRNP70 small nuclear 1 x SLE vs ribonucleoprotein AID 70 kDa (U1) 13 6628 SNRPB small nuclear 1 x x x SLE vs ribonucleoprotein AID polypeptides B and B1 14 6638 SNRPN small nuclear 1 x SLE vs ribonucleoprotein AID polypeptide N 15 6672 SP100 SP100 nuclear 1 x x SLE vs antigen AID 16 6710 SPTB spectrin, beta, 1 x x SLE vs erythrocytic AID 17 6741 SSB Sjogren syndrome 1 x x SLE vs antigen B AID (autoantigen La) 18 7112 TMPO thymopoietin 1 x x x SLE vs AID 19 6737 TRIM21 tripartite motif- 1 x x x SLE vs containing 21 AID 20 6738 TROVE2 TROVE domain 1 x x SLE vs family, member 2 RA 21 7431 VIM vimentin 1 x x SLE vs AID 22 7520 XRCC5 X-ray repair 1 x x SLE vs complementing AID defective repair in Chinese hamster cells 5 (double- strand-break rejoining) 23 7764 ZNF217 zinc finger protein 1 x x SLE vs 217 AID 24 64763 ZNF574 zinc finger protein 1 x x SLE vs 574 AID 25 148741 ANKRD35 ankyrin repeat 2 x x SLE vs domain 35 HV 26 84779 ARD1B ARD1 homolog B (S. 2 x x SLE vs cerevisiae) AID 27 672 BRCA1 breast cancer 1, 2 x x SLE vs early onset HV 28 134359 C5orf37 chromosome 5 open 2 x x x SLE vs reading frame 37 HV 29 9478 CABP1 calcium binding 2 x x SLE vs protein 1 HV 30 90557 CCDC74A coiled-coil domain 2 x x SLE vs containing 74A HV 31 9973 CCS copper chaperone 2 x x x x SLE vs for superoxide AID dismutase 32 1410 CRYAB crystallin, alpha B 2 x x SLE vs HV 33 55802 DCP1A DCP1 decapping 2 x x SLE vs enzyme homolog A HV (S. cerevisiae) 34 79147 FKRP fukutin related 2 x x SLE vs protein HV 35 26128 KIAA1279 KIAA1279 2 x x SLE vs HV 36 57608 KIAA1462 KIAA1462 2 x x SLE vs HV 37 1939 LGTN ligatin 2 x x SLE vs HV 38 84298 LLPH LLP homolog, long- 2 x x SLE vs term synaptic HV facilitation (Aplysia) 39 11253 MAN1B1 mannosidase, alpha, 2 x x SLE vs class 1B, member 1 HV 40 84930 MASTL microtubule 2 x x SLE vs associated HV serine/threonine kinase-like 41 54531 MIER2 mesorm induction 2 x x x x SLE vs early response 1, RA family member 2 42 4594 MUT methylmalonyl 2 x x SLE vs Coenzyme A mutase HV 43 399687 MYO18A myosin XVIIIA 2 x x SLE vs HV 44 8883 NAE1 NEDD8 activating 2 x x SLE vs enzyme E1 subunit 1 HV 45 10458 BAIAP2 BAI1-associated 2 x x SLE vs protein 2 HV 46 4869 NPM1 nucleophosmin 2 x x SLE vs (nucleolar HV phosphoprotein B23, numatrin) 47 5223 PGAM1 phosphoglycerate 2 x x SLE vs mutase 1 (brain) HV 48 11040 PIM2 pim-2 oncogene 2 x x SLE vs HV 49 54517 PUS7 pseudouridylate 2 x x SLE vs synthase 7 homolog HV (S. cerevisiae) 50 6605 SMARCE1 SWI/SNF related, 2 x x SLE vs matrix associated, AID actin dependent regulator of chromatin, subfamily e, member 1 51 23635 SSBP2 single-stranded DNA 2 x x x SLE vs binding protein 2 HV 52 83660 TLN2 talin 2 2 x x SLE vs HV 53 51673 TPPP3 tubulin 2 x x SLE vs polymerization- HV promoting protein family member 3 54 7265 TTC1 tetratricopeptide 2 x x SLE vs repeat domain 1 HV 55 124930 ANKRD13B ankyrin repeat 3 x SLE vs domain 13B HV 56 160 AP2A1 adaptor-related 3 x SLE vs protein complex 2, HV alpha 1 subunit 57 53335 BCL11A B-cell CLL/lymphoma 3 x x 11A (zinc finger protein) 58 79959 CEP76 centrosomal protein 3 x 76 kDa 59 1153 CIRBP cold inducible RNA 3 x SLE vs binding protein HV 60 51084 CRYL1 crystallin, lambda 3 x 1 61 55827 DCAF6 DDB1 and CUL4 3 x x x SLE vs associated factor 6 AID 62 6993 DYNLT1 dynein, light 3 x SLE vs chain, Tctex-type 1 HV 63 283991 FAM100B family with 3 x SLE vs sequence similarity HV 100, member B 64 9815 GIT2 G protein-coupled 3 x SLE vs receptor kinase HV interacting ArfGAP 2 65 84706 GPT2 glutamic pyruvate 3 x transaminase (alanine aminotransferase) 2 66 3059 HCLS1 hematopoietic cell- 3 x x SLE vs specific Lyn AID substrate 1 67 3329 HSPD1 heat shock 60 kDa 3 x protein 1 (chaperonin) 68 3490 IGFBP7 insulin-like growth 3 x SLE vs factor binding HV protein 7 69 23392 KIAA0368 KIAA0368 3 x 70 84695 LOXL3 lysyl oxidase-like 3 x 3 71 4133 MAP2 microtubule- 3 x SLE vs associated protein RA 2 72 6837 MED22 mediator complex 3 x subunit 22 73 29079 MED4 mediator complex 3 x x subunit 4 74 10933 MORF4L1 mortality factor 4 3 x like 1 75 64963 MRPS11 mitochondrial 3 x x SLE vs ribosomal protein HV S11 76 81565 NDEL1 nudE nuclear 3 x distribution gene E homolog (A. nidulans)-like 1 77 57447 NDRG2 NDRG family member 3 x SLE vs 2 HV 78 4744 NEFH neurofilament, 3 x heavy polypeptide 79 153478 PLEKHG4B pleckstrin homology 3 x SLE vs domain containing, RA family G (with RhoGef domain) member 4B [homo sapiens (human)] 80 11054 OGFR opioid growth 3 x x SLE vs factor receptor AID 81 56122 PCDHB14 protocadherin beta 3 x SLE vs 14 HV 82 2923 PDIA3 protein disulfide 3 x SLE vs isomerase family A, HV member 3 83 23646 PLD3 phospholipase D 3 x SLE vs family, member 3 HV 84 23759 PPIL2 peptidylprolyl 3 x isomerase (cyclophilin)-like 2 85 5557 PRIM1 primase, DNA, 3 x x polypeptide 1 (49 kDa) 86 5682 PSMA1 proteasome 3 x SLE vs (prosome, HV macropain) subunit, alpha type, 1 87 5802 PTPRS protein tyrosine 3 x SLE vs phosphatase, HV receptor type, S 88 81890 QTRT1 queuine tRNA- 3 x SLE vs ribosyltransferase HV 1 89 116362 RBP7 retinol binding 3 x SLE vs protein 7, cellular HV 90 10287 RGS19 regulator of G- 3 x x protein signaling 19 91 83642 RP3- selenoprotein O 3 x SLE vs 402G11.5 HV 92 6389 SDHA succinate 3 x x SLE vs dehydrogenase AID complex, subunit A, flavoprotein (Fp) 93 54437 SEMA5B sema domain, seven 3 x thrombospondin repeats (type 1 and type 1-like), transmembrane domain (TM) and short cytoplasmic domain, (semaphorin) 5B 94 59343 SENP2 SUMO1/sentrin/SMT3 3 x SLE vs specific peptidase HV 2 95 6629 SNRPB2 small nuclear 3 x SLE vs ribonucleoprotein AID polypeptide B′′ 96 27131 SNX5 sorting nexin 5 3 x SLE vs HV 97 9021 SOCS3 suppressor of 3 x x SLE vs cytokine signaling HV 3 98 3925 STMN1 stathmin 1 3 x SLE vs HV 99 81551 STMN4 stathmin-like 4 3 x SLE vs HV 100 27097 TAF5L TAF5-like RNA 3 x SLE vs polymerase II, HV p300/CBP-associated factor (PCAF)- associated factor, 65 kDa 101 79921 TCEAL4 transcription 3 x SLE vs elongation factor A HV (SII)-like 4 102 10040 TOM1L1 target of myb1 3 x SLE vs (chicken)-like 1 HV 103 22974 TPX2 TPX2, microtubule- 3 x SLE vs associated, homolog HV (Xenopus laevis) 104 51567 TTRAP TRAF and TNF 3 x receptor associated protein 105 8615 USO1 USO1 homolog, 3 x x vesicle docking protein (yeast) 106 10869 USP19 ubiquitin specific 3 x SLE vs peptidase 19 RA 107 29761 USP25 ubiquitin specific 3 x peptidase 25 108 375690 WASH5P WAS protein family 3 x x SLE vs homolog 5 HV pseudogene 109 10413 YAP1 Yes-associated 3 x protein 1, 65 kDa 110 653121 ZBTB8A zinc finger and BTB 3 x x SLE vs domain containing HV 8A 111 55311 ZNF444 zinc finger protein 3 x 444 112 29 ABR active BCR-related 4 x SLE vs gene AID 113 118 ADD1 adducin 1 (alpha) 4 x SLE vs AID 114 55256 ADI1 acireductone 4 x SLE vs dioxygenase 1 HV 115 9255 AIMP1 aminoacyl tRNA 4 x synthetase complex- interacting multifunctional protein 1 116 54522 ANKRD16 ankyrin repeat 4 x SLE vs domain 16 HV 117 348 APOE apolipoprotein E 4 x SLE vs HV 118 64333 ARHGAP9 Rho GTPase 4 x SLE vs activating protein HV 9 119 22994 AZI1 5-azacytidine 4 x SLE vs induced 1 HV 120 55971 BAIAP2L1 BAI1-associated 4 x protein 2-like 1 121 7919 BAT1 HLA-B associated 4 x SLE vs transcript 1 RA 122 6046 BRD2 bromodomain 4 x containing 2 123 56912 C11orf60 chromosome 11 open 4 x reading frame 60 124 79415 C17orf62 chromosome 17 open 4 x reading frame 62 125 51300 C3orf1 chromosome 3 open 4 x SLE vs reading frame 1 RA 126 128866 CHMP4B chromatin modifying 4 x SLE vs protein 4B AID 127 23152 CIC capicua homolog 4 x SLE vs (Drosophila) AID 128 10970 CKAP4 cytoskeleton- 4 x SLE vs associated protein HV 4 129 23122 CLASP2 cytoplasmic linker 4 x SLE vs associated protein HV 2 130 1311 COMP cartilage 4 x oligomeric matrix protein 131 7812 CSDE1 cold shock domain 4 x SLE vs containing E1, RNA- HV binding 132 8642 DCHS1 dachsous 1 4 x SLE vs (Drosophila) AID 133 9909 DENND4B DENN/MADD domain 4 x x containing 4B 134 1743 DLST dihydrolipoamide S- 4 x succinyltransferase (E2 component of 2- oxo-glutarate complex) 135 84444 DOT1L DOT1-like, histone 4 x H3 methyltransferase (S. cerevisiae) 136 51143 DYNC1LI1 dynein, cytoplasmic 4 x SLE vs 1, light HV intermediate chain 1 137 51011 FAHD2A fumarylacetoacetate 4 x hydrolase domain containing 2A 138 92689 FAM114A1 family with 4 x sequence similarity 114, member A1 139 54463 FAM134B family with 4 x sequence similarity 134, member B 140 100129583 FAM47E family with 4 x SLE vs sequence similarity HV 47, member E 141 93611 FBXO44 F-box protein 44 4 x 142 60681 FKBP10 FK506 binding 4 x SLE vs protein 10, 65 kDa AID 143 23360 FNBP4 formin binding 4 x SLE vs protein 4 HV 144 2300 FOXL1 forkhead box L1 4 x SLE vs HV 145 64689 GORASP1 golgi reassembly 4 x SLE vs stacking protein 1, AID 65 kDa 146 2934 GSN gelsolin 4 x SLE vs (amyloidosis, HV Finnish type) 147 3039 HBA1 hemoglobin, alpha 1 4 x 148 3040 HBA2 hemoglobin, alpha 2 4 x 149 388585 HES5 hairy and enhancer 4 x of split 5 (Drosophila) 150 10525 HYOU1 hypoxia up- 4 x regulated 1 151 3608 ILF2 interleukin 4 x SLE vs enhancer binding RA factor 2, 45 kDa 152 23135 KDM6B lysine (K)-specific 4 x SLE vs demethylase 6B AID 153 56243 KIAA1217 KIAA1217 4 x SLE vs HV 154 57662 KIAA1543 KIAA1543 4 x 155 57498 KIDINS220 kinase D- 4 x interacting substrate, 220 kDa 156 3855 KRT7 keratin 7 4 x SLE vs HV 157 729970 LOC729970 similar to 4 x hCG2028352 158 9935 MAFB v-maf 4 x musculoaponeurotic fibrosarcoma oncogene homolog B (avian) 159 23764 MAFF v-maf 4 x SLE vs musculoaponeurotic HV fibrosarcoma oncogene homolog F (avian) 160 22924 MAPRE3 microtubule- 4 x associated protein, RP/EB family, member 3 161 8079 MLF2 myeloid leukemia 4 x factor 2 162 4676 NAP1L4 nucleosome assembly 4 x protein 1-like 4 163 4688 NCF2 neutrophil 4 x SLE vs cytosolic factor 2 HV 164 4780 NFE2L2 nuclear factor 4 x (erythroid-derived 2)-like 2 165 79840 NHEJ1 nonhomologous end- 4 x x joining factor 1 166 22861 NLRP1 NLR family, pyrin 4 x SLE vs domain containing 1 HV 167 65009 NDRG4 NDRG family member 4 4 x SLE vs HV 168 4841 NONO non-POU domain 4 x SLE vs containing, AID octamer-binding 169 29982 NRBF2 nuclear receptor 4 x SLE vs binding factor 2 AID 170 8439 NSMAF neutral 4 x SLE vs sphingomyelinase HV (N-SMase) activation associated factor 171 4926 NUMA1 nuclear mitotic 4 x SLE vs apparatus protein 1 RA 172 84759 PCGF1 polycomb group ring 4 x finger 1 173 84306 PDCD2L programmed cell 4 x SLE vs death 2-like HV 174 5195 PEX14 peroxisomal 4 x SLE vs biogenesis factor HV 14 175 9091 PIGQ phosphatidylinositol 4 x SLE vs glycan anchor RA biosynthesis, class Q 176 100137049 PLA2G4B phospholipase A2, 4 x SLE vs group IVB RA (cytosolic) 177 10226 PLIN3 perilipin 3 4 x 178 5373 PMM2 phosphomannomutase 4 x 2 179 10450 PPIE peptidylprolyl 4 x isomerase E (cyclophilin E) 180 5694 PSMB6 proteasome 4 x (prosome, macropain) subunit, beta type, 6 181 22913 RALY RNA binding 4 x SLE vs protein, HV autoantigenic (hnRNP-associated with lethal yellow homolog (mouse)) 182 8241 RBM10 RNA binding motif 4 x protein 10 183 9904 RBM19 RNA binding motif 4 x SLE vs protein 19 HV 184 9743 RICS Rho GTPase- 4 x activating protein 185 8780 RIOK3 RIO kinase 3 4 x (yeast) 186 8578 SCARF1 scavenger receptor 4 x SLE vs class F, member 1 AID 187 23513 SCRIB scribbled homolog 4 x SLE vs (Drosophila) HV 188 644096 SDHAF1 succinate 4 x SLE vs dehydrogenase RA complex assembly factor 1 57794 SF4 splicing factor 4 4 x SLE vs RA 189 9814 SFI1 Sfi1 homolog, 4 x spindle assembly associated (yeast) 190 6421 SFPQ splicing factor 4 x SLE vs proline/glutamine- AID rich (polypyrimidine tract binding protein associated) 191 83442 SH3BGRL3 SH3 domain binding 4 x glutamic acid-rich protein like 3 192 6461 SHB Src homology 2 4 x SLE vs domain containing AID adaptor protein B 193 23381 SMG5 Smg-5 homolog, 4 x SLE vs nonsense mediated HV mRNA decay factor (C. elegans) 194 112574 SNX18 sorting nexin 18 4 x SLE vs HV 195 84501 SPIRE2 spire homolog 2 4 x SLE vs (Drosophila) HV 196 54961 SSH3 slingshot homolog 3 4 x SLE vs (Drosophila) AID 197 9263 STK17A serine/threonine 4 x kinase 17a 198 51111 SUV420H1 suppressor of 4 x variegation 4-20 homolog 1 (Drosophila) 199 6902 TBCA tubulin folding 4 x cofactor A 200 7024 TFCP2 transcription 4 x SLE vs factor CP2 HV 201 7030 TFE3 transcription 4 x SLE vs factor binding to HV IGHM enhancer 3 202 90326 THAP3 THAP domain 4 x SLE vs containing, AID apoptosis associated protein 3 203 10043 TOM1 target of myb1 4 x (chicken) 204 7168 TPM1 tropomyosin 1 4 x SLE vs (alpha) HV 205 54952 TRNAU1AP tRNA selenocysteine 4 x 1 associated protein 1 206 26140 TTLL3 tubulin tyrosine 4 x ligase-like family, member 3 207 7371 UCK2 uridine-cytidine 4 x SLE vs kinase 2 HV 208 9277 WDR46 WD repeat domain 46 4 x SLE vs HV 209 55100 WDR70 WD repeat domain 70 4 x SLE vs AID 210 23038 WDTC1 WD and 4 x SLE vs tetratricopeptide HV repeats 1 211 9831 ZNF623 zinc finger protein 4 x 623 212 79364 ZXDC ZXD family zinc 4 x x SLE vs finger C AID 213 7791 ZYX zyxin 4 x SLE vs AID 214 55964 SEPT3 septin 3 5 x 215 5413 SEPT5 septin 5 5 x 216 26574 AATF apoptosis 5 x antagonizing transcription factor 217 91703 ACY3 aspartoacylase 5 x (aminocyclase) 3 218 9509 ADAMTS2 ADAM 6 SLE vs metallopeptidase RA with thrombospondin type 1 motif, 2 219 10939 AFG3L2 AFG3 ATPase family 6 SLE vs gene 3-like 2 HV (yeast) 220 1646 AKR1C2 aldo-keto reductase 6 SLE vs family 1, member C2 RA (dihydrodiol dehydrogenase 2; bile acid binding protein; 3-alpha hydroxysteroid dehydrogenase, type III) 221 267 AMFR autocrine motility 6 SLE vs factor receptor RA 222 10777 ARPP- cyclic AMP- 6 SLE vs 21 regulated RA phosphoprotein, 21 kD 223 421 ARVCF armadillo repeat 6 SLE vs gene deletes in RA velocardiofacial syndrome 224 80150 ASRGL1 asparaginase like 1 6 SLE vs RA 225 539 ATP5O ATP synthase, H+ 6 SLE vs transporting, RA mitochondrial F1 complex, O subunit 226 79870 BAALC brain and acute 6 SLE vs leukemia, RA cytoplasmic 227 9531 BAG3 BCL2-associated 5 x athanogene 3 228 9275 BCL7B B-cell CLL/lymphoma 6 SLE vs 7B HV 229 55108 BSDC1 BSD domain 6 SLE vs containing 1 AID 230 54934 C12orf41 chromosome 12 open 6 SLE vs reading frame 41 RA 231 55049 C19orf60 chromosome 19 open 6 SLE vs reading frame 60 RA 232 388799 C20orf107 chromosome 20 open 5 x reading frame 107 233 149840 C20orf196 chromosome 20 open 6 SLE vs reading frame 196 RA 234 51507 C20orf43 chromosome 20 open 6 SLE vs reading frame 43 RA 235 55684 C9orf86 chromosome 9 open 6 SLE vs reading frame 86 HV 236 23523 CABIN1 calcineurin binding 6 SLE vs protein 1 RA 237 157922 CAMSAP1 calmodulin 6 SLE vs regulated spectrin- RA associated protein 1 238 23624 CBLC Cas-Br-M (murine) 6 SLE vs ecotropic HV retroviral transforming sequence c 239 124808 CCDC43 coiled-coil domain 6 SLE vs containing 43 RA 240 100133941 CD24 CD24 molecule 5 x 241 11140 CDC37 cell division cycle 6 SLE vs 37 homolog (S. RA cerevisiae) 242 10153 CEBPZ CCAAT/enhancer 6 SLE vs binding protein RA (C/EBP), zeta 243 51510 CHMP5 chromatin modifying 6 SLE vs protein 5 RA 244 63922 CHTF18 CTF18, chromosome 5 x transmission fidelity factor 18 homolog (S. cerevisiae) 245 51727 CMPK1 cytidine 6 SLE vs monophosphate (UMP- AID CMP) kinase 1, cytosolic 246 64708 COPS7B COP9 constitutive 5 x photomorphogenic homolog subunit 7B (Arabidopsis) 247 51117 COQ4 coenzyme Q4 homolog 6 SLE vs (S. cerevisiae) RA 248 27254 CSDC2 cold shock domain 5 x containing C2, RNA binding 249 162989 DEDD2 death effector 6 SLE vs domain containing 2 RA 250 9704 DHX34 DEAH (Asp-Glu-Ala- 6 SLE vs His) box RA polypeptide 34 251 55837 EAPP E2F-associated 6 SLE vs phosphoprotein RA 252 1915 EEF1A1 eukaryotic 6 SLE vs translation RA elongation factor 1 alpha 1 253 1936 EEF1D eukaryotic 6 SLE vs translation RA elongation factor 1 delta (guanine nucleotide exchange protein) 254 8669 EIF3J eukaryotic 6 SLE vs translation RA initiation factor 3, subunit J 255 55740 ENAH enabled homolog 6 SLE vs (Drosophila) HV 256 2023 ENO1 enolase 1, (alpha) 6 SLE vs HV 257 11124 FAF1 Fas (TNFRSF6) 5 x associated factor 1 258 11170 FAM107A family with 6 SLE vs sequence similarity HV 107, member A 259 84908 FAM136A family with 6 SLE vs sequence similarity RA 136, member A 260 10144 FAM13A family with 6 SLE vs sequence similarity RA 13, member A 261 26017 FAM32A family with 6 SLE vs sequence similarity HV 32, member A 262 64762 FAM59A family with 6 SLE vs sequence similarity RA 59, member A 263 150946 FAM59B family with 6 SLE vs sequence similarity HV 59, member B 264 83706 FERMT3 fermitin family 6 SLE vs homolog 3 RA (Drosophila) 265 23307 FKBP15 FK506 binding 6 SLE vs protein 15, 133 kDa HV 266 2670 GFAP glial fibrillary 6 SLE vs acidic protein RA 267 51031 GLOD4 glyoxalase domain 6 SLE vs containing 4 AID 268 81488 GRINL1A glutamate receptor, 6 SLE vs ionotropic, N- RA methyl D-aspartate- like 1A 269 2922 GRP gastrin-releasing 6 SLE vs peptide RA 270 2935 GSPT1 G1 to S phase 6 SLE vs transition 1 RA 271 93323 HAUS8 HAUS augmin-like 6 SLE vs complex, subunit 8 HV 272 3054 HCFC1 host cell factor C1 6 SLE vs (VP16-accessory AID protein) 273 3069 HDLBP high density 6 SLE vs lipoprotein binding RA protein 274 3184 HNRNPD heterogeneous 6 SLE vs nuclear HV ribonucleoprotein D (AU-rich element RNA binding protein 1, 37 kDa) 275 3320 HSP90AA1 heat shock protein 6 SLE vs 90 kDa alpha RA (cytosolic), class A member 1 276 7184 HSP90B1 heat shock protein 6 SLE vs 90 kDa beta (Grp94), RA member 1 277 3304 HSPA1B heat shock 70 kDa 6 SLE vs protein 1B RA 278 3315 HSPB1 heat shock 27 kDa 4 x x SLE vs protein 1 RA 279 5654 HTRA1 HtrA serine 6 SLE vs peptidase 1 RA 280 3382 ICA1 islet cell 6 SLE vs autoantigen 1, RA 69 kDa 281 3550 IK IK cytokine, down- 6 SLE vs regulator of HLA II HV 282 80895 ILKAP integrin-linked 6 SLE vs kinase-associated RA serine/threonine phosphatase 2C 283 84162 KIAA1109 KIAA1109 6 SLE vs AID 284 3856 KRT8 keratin 8 6 SLE vs RA 285 23367 LARP1 La 6 SLE vs ribonucleoprotein AID domain family, member 1 286 4001 LMNB1 lamin B1 6 SLE vs RA 287 79888 LPCAT1 lysophosphatidylcho- 5 x SLE vs line HV acyltransferase 1 288 10916 MAGED2 melanoma antigen 5 x family D, 2 289 55700 MAP7D1 MAP7 domain 6 SLE vs containing 1 RA 290 5602 MAPK10 mitogen-activated 6 SLE vs protein kinase 10 HV 291 22919 MAPRE1 microtubule- 6 SLE vs associated protein, AID RP/EB family, member 1 292 4137 MAPT microtubule- 6 SLE vs associated protein RA tau 293 23139 MAST2 microtubule 6 SLE vs associated RA serine/threonine kinase 2 294 53615 MBD3 methyl-CpG binding 6 SLE vs domain protein 3 RA 295 56922 MCCC1 methylcrotonoyl- 6 SLE vs Coenzyme A HV carboxylase 1 (alpha) 296 1953 MEGF6 multiple EGF-like- 6 SLE vs domains 6 RA 297 4302 MLLT6 myeloid/lymphoid or 6 SLE vs mixed-lineage RA leukemia (trithorax homolog, Drosophila); translocated to, 6 298 10200 MPHOSPH6 M-phase 6 SLE vs phosphoprotein 6 RA 299 10240 MRPS31 mitochondrial 6 SLE vs ribosomal protein HV S31 300 84939 MUM1 melanoma associated 5 x antigen (mutated) 1 301 4599 MX1 myxovirus 6 SLE vs (influenza virus) RA resistance 1, interferon- inducible protein p78 (mouse) 302 4716 NDUFB10 NADH dehydrogenase 6 SLE vs (ubiquinone) 1 beta RA subcomplex, 10, 22 kDa 303 4796 NFKBIL2 nuclear factor of 6 SLE vs kappa light HV polypeptide gene enhancer in B-cells inhibitor-like 2 304 11188 NISCH nischarin 6 SLE vs RA 305 10381 TUBB3 tubulin, beta 3 6 SLE vs class III RA 306 8602 NOP14 NOP14 nucleolar 6 SLE vs protein homolog RA (yeast) 307 9722 NOS1AP nitric oxide 6 SLE vs synthase 1 RA (neuronal) adaptor protein 308 29959 NRBP1 nuclear receptor 5 x binding protein 1 309 142 PARP1 poly (ADP-ribose) 6 SLE vs polymerase 1 RA 310 5091 PC pyruvate 6 SLE vs carboxylase RA 311 23024 PDZRN3 PDZ domain 6 SLE vs containing ring RA finger 3 312 8682 PEA15 phosphoprotein 6 SLE vs enriched in RA astrocytes 15 313 5187 PER1 period homolog 1 6 SLE vs (Drosophila) HV 314 57649 PHF12 PHD finger protein 5 x 12 315 26227 PHGDH phosphoglycerate 5 x dehydrogenase 316 1263 PLK3 polo-like kinase 3 6 SLE vs (Drosophila) RA 317 23654 PLXNB2 plexin B2 6 SLE vs RA 318 56902 PNO1 partner of NOB1 6 SLE vs homolog (S. RA cerevisiae) 319 5479 PPIB peptidylprolyl 6 SLE vs isomerase B HV (cyclophilin B) 320 56978 PRDM8 PR domain 6 SLE vs containing 8 HV 321 55119 PRPF38B PRP38 pre-mRNA 6 SLE vs processing factor RA 38 (yeast) domain containing B 322 5764 PTN pleiotrophin 6 SLE vs HV 323 5819 PVRL2 poliovirus 5 x receptor-related 2 (herpesvirus entry mediator B) 324 5831 PYCR1 pyrroline-5- 6 SLE vs carboxylate RA reductase 1 325 65997 RASL11B RAS-like, family 6 SLE vs 11, member B RA 326 55658 RNF126 ring finger protein 6 SLE vs 126 AID 327 115992 RNF166 ring finger protein 6 SLE vs 166 HV 328 9025 RNF8 ring finger protein 6 SLE vs 8 HV 329 6092 ROBO2 roundabout, axon 5 x guidance receptor, homolog 2 (Drosophila) 330 64221 ROBO3 roundabout, axon 5 x guidance receptor, homolog 3 (Drosophila) 331 4736 RPL10A ribosomal protein 6 SLE vs L10a RA 332 6152 RPL24 ribosomal protein 6 SLE vs L24 RA 333 148418 SAMD13 sterile alpha motif 6 SLE vs domain containing HV 13 334 57147 SCYL3 SCY1-like 3 (S. 6 SLE vs cerevisiae) AID 335 6382 SDC1 syndecan 1 6 SLE vs RA 336 91461 SGK493 protein kinase-like 5 x protein SgK493 337 6449 SGTA small glutamine- 6 SLE vs rich HV tetratricopeptide repeat (TPR)- containing, alpha 338 9627 SNCAIP synuclein, alpha 5 x interacting protein 339 9552 SPAG7 sperm associated 6 SLE vs antigen 7 RA 340 57522 SRGAP1 SLIT-ROBO Rho 6 SLE vs GTPase activating RA protein 1 341 6744 SSFA2 sperm specific 6 SLE vs antigen 2 RA 342 6487 ST3GAL3 ST3 beta- 6 SLE vs galactoside alpha- RA 2,3- sialyltransferase 3 343 23345 SYNE1 spectrin repeat 6 SLE vs containing, nuclear AID envelope 1 344 6879 TAF7 TAF7 RNA polymerase 6 SLE vs II, TATA box HV binding protein (TBP)-associated factor, 55 kDa 345 6895 TARBP2 TAR (HIV-1) RNA 6 SLE vs binding protein 2 RA 346 6949 TCOF1 Treacher Collins- 6 SLE vs Franceschetti RA syndrome 1 347 7980 TFPI2 tissue factor 5 x pathway inhibitor 2 348 56674 TMEM9B TMEM9 domain 6 SLE vs family, member B RA 349 11189 TNRC4 trinucleotide 5 x repeat containing 4 350 10155 TRIM28 tripartite motif- 6 SLE vs containing 28 HV 351 7204 TRIO triple functional 6 SLE vs domain (PTPRF RA interacting) 352 203068 TUBB tubulin, beta 6 SLE vs RA 353 7280 TUBB2A tubulin, beta 2A 6 SLE vs RA 354 27229 TUBGCP4 tubulin, gamma 6 SLE vs complex associated RA protein 4 355 10422 UBAC1 UBA domain 6 SLE vs containing 1 RA 356 7316 UBC ubiquitin C 6 SLE vs RA 357 55585 UBE2Q1 ubiquitin- 6 SLE vs conjugating enzyme HV E2Q family member 1 358 65109 UPF3B UPF3 regulator of 5 x nonsense transcripts homolog B (yeast) 359 7378 UPP1 uridine 6 SLE vs phosphorylase 1 AID 360 64856 VWA1 von Willebrand 6 SLE vs factor A domain RA containing 1 361 55884 WSB2 WD repeat and SOCS 5 x box-containing 2 362 9877 ZC3H11A zinc finger CCCH- 5 x type containing 11A 363 55854 ZC3H15 zinc finger CCCH- 6 SLE vs type containing 15 HV 364 7592 ZNF41 zinc finger protein 6 SLE vs 41 RA 365 170959 ZNF431 zinc finger protein 6 SLE vs 431 RA 366 146542 ZNF688 zinc finger protein 6 SLE vs 688 RA 367 4670 HNRNPM heterogeneous 7 SLE vs nuclear HV ribonucleoprotein M 368 10540 DCTN2 dynactin 2 (p50) 7 SLE vs HV 369 10938 EHD1 EH-domain 7 SLE vs containing 1 HV 370 38 ACAT1 Acetyl-Coenzyme A 7 SLE vs acetyltransferase 1 HV (acetoacetyl Coenzyme A thiolase) 371 684 BST2 bone marrow stromal 7 SLE vs cell antigen 2 HV 372 1058 CENPA centromere protein 7 SLE vs A HV 373 1665 DHX15 DEAH (Asp-Glu-Ala- 7 SLE vs His) box HV polypeptide 15 374 3092 HIP1 Huntingtin 7 SLE vs interacting protein HV 1 375 3336 HSPE1 heat shock 10 kDa 7 SLE vs protein 1 HV (chaperonin 10) 376 5455 POU3F3 POU class 3 7 SLE vs homeobox 3 HV 377 5918 RARRES1 retinoic acid 7 SLE vs receptor responder HV (tazarotene induced) 1 378 6136 RPL12 ribosomal protein 7 SLE vs L12 HV 379 6626 SNRPA small nuclear 7 SLE vs ribonucleoprotein HV polypeptide A 380 6631 SNRPC small nuclear 7 SLE vs ribonucleoprotein HV polypeptide C 381 6757 SSX2 synovial sarcoma, X 7 SLE vs breakpoint 2 HV 382 9788 MTSS1 metastasis 7 SLE vs suppressor 1 HV 383 10134 BCAP31 B-cell receptor- 7 SLE vs associated protein HV 31 384 10522 DEAF1 deformed epidermal 7 SLE vs autoregulatory HV factor 1 (Drosophila) 385 10633 RASL10A RAS-like, family 7 SLE vs 10, member A HV 386 54795 TRPM4 transient receptor 7 SLE vs potential cation HV channel, subfamily M, member 4 387 54913 RPP25 ribonuclease P/MRP 7 SLE vs 25 kDa subunit HV 388 54994 C20orf11 chromosome 20 open 7 SLE vs reading frame 11 HV 389 55727 BTBD7 BTB (POZ) domain 7 SLE vs containing 7 HV 390 79140 CCDC28B coiled-coil domain 7 SLE vs containing 28B HV 391 79613 TMCO7 transmembrane and 7 SLE vs coiled-coil domains HV 7 392 5504 PPP1R2 protein phosphatase 7 SLE vs 1, regulatory HV (inhibitor) subunit 2 393 8349 HIST2H2BE histone cluster 2, 7 SLE vs H2be HV 394 11168 PSIP1 PC4 and SFRS1 7 SLE vs interacting protein HV 1 395 149986 LSM14B LSM14B, SCD6 7 SLE vs homolog B (S. HV cerevisiae) 396 655 BMP7 Bone morphogenetic 7 SLE vs protein 7 HV (osteogenic protein 1) 397 1676 DFFA DNA fragmentation 7 SLE vs factor, 45 kDa, HV alpha polypeptide 398 3071 NCKAP1L NCK-associated 7 SLE vs protein 1-like HV 399 3727 JUND jun D proto- 7 SLE vs oncogene HV 400 3960 LGALS4 lectin, 7 SLE vs galactoside- HV binding, soluble, 4 401 4920 ROR2 Receptor tyrosine 7 SLE vs kinase-like orphan HV receptor 2 402 7424 VEGFC vascular 7 SLE vs endothelial growth HV factor C 403 8906 AP1G2 adaptor-related 7 SLE vs protein complex 1, HV gamma 2 subunit 404 10297 APC2 adenomatosis 7 SLE vs polyposis coli 2 HV 405 10841 FTCD Formiminotransferase 7 SLE vs cyclodeaminase HV 406 11066 SNRNP35 small nuclear 7 SLE vs ribonucleoprotein HV 35 kDa (U11/U12) 407 11345 GABARAPL2 GABA(A) receptor- 7 SLE vs associated protein- HV like 2 408 25854 FAM149A family with 7 SLE vs sequence similarity HV 149, member A 409 26065 LSM14A LSM14A, SCD6 7 SLE vs homolog A (S. HV cerevisiae) 410 28998 MRPL13 mitochondrial 7 SLE vs ribosomal protein HV L13 411 51520 LARS leucyl-tRNA 7 SLE vs synthetase HV 412 55747 FAM21B family with 7 SLE vs sequence similarity HV 21, member B 413 64841 GNPNAT1 glucosamine- 7 SLE vs phosphate N- HV acetyltransferase 1 414 83483 PLVAP Plasmalemma vesicle 7 SLE vs associated protein HV 415 84968 PNMA6A paraneoplastic 7 SLE vs antigen like 6A HV 416 118430 MUCL1 Mucin-like 1 7 SLE vs HV 417 122830 NAT12 N-acetyltransferase 7 SLE vs 12 HV 418 221092 HNRNPUL2 heterogeneous 7 SLE vs nuclear HV ribonucleoprotein U-like 2 419 388962 BOLA3 bolA homolog 3 (E. 7 SLE vs coli) HV 420 729230 FLJ78302 Similar to C-C 7 SLE vs chemokine receptor HV type 2 (C-C CKR-2) (CC-CKR-2) (CCR-2) (CCR2) (Monocyte chemoattractant protein 1 receptor) (MCP-1-R) (CD192 antigen) 421 729447 GAGE2A G antigen 2A 7 SLE vs HV 422 1152 CKB No Gene Name; 7 SLE vs creatine kinase, HV brain 423 972 CD74 CD74 molecule, 7 SLE vs major HV histocompatibility complex, class II invariant chain 424 1397 CRIP2 cysteine-rich 7 SLE vs protein 2 HV 425 2040 STOM stomatin 7 SLE vs HV 426 2316 FLNA filamin A, alpha 7 SLE vs HV 427 4000 LMNA lamin A/C 7 SLE vs HV 428 4582 MUC1 mucin 1, cell 7 SLE vs surface associated HV 429 5230 PGK1 Phosphoglycerate 7 SLE vs kinase 1 HV 430 5340 PLG plasminogen 7 SLE vs HV 431 6525 SMTN smoothelin 7 SLE vs HV 432 8936 WASF1 WAS protein family, 7 SLE vs member 1 HV 433 23647 ARFIP2 ADP-ribosylation 7 SLE vs factor interacting HV protein 2 434 6712 SPTBN2 spectrin, beta, 7 SLE vs non-erythrocytic 2 HV 435 6729 SRP54 signal recognition 7 SLE vs particle 54 kDa HV 436 9987 HNRPDL heterogeneous 7 SLE vs nuclear HV ribonucleoprotein D-like 437 337 APOA4 Apolipoprotein A-IV 7 SLE vs HV 438 950 SCARB2 scavenger receptor 7 SLE vs class B, member 2 HV 439 3183 HNRNPC heterogeneous 7 SLE vs nuclear HV ribonucleoprotein C (C1/C2) 440 3185 HNRPF Heterogeneous 7 SLE vs nuclear HV ribonucleoprotein F 441 3313 HSPA9 heat shock 70 kDa 7 SLE vs protein 9 HV (mortalin) 442 3467 IFNW1 Interferon, omega 1 7 SLE vs HV 443 3799 KIF5B kinesin family 7 SLE vs member 5B HV 444 7918 BAT4 HLA-B associated 7 SLE vs transcript 4 HV 445 8337 HIST2H2AA3 histone cluster 2, 7 SLE vs H2aa3 HV 446 10195 ALG3 asparagine-linked 7 SLE vs glycosylation 3, HV alpha-1,3- mannosyltransferase homolog (S. cerevisiae) 447 23299 BICD2 bicaudal D homolog 7 SLE vs 2 (Drosophila) HV 448 80184 CEP290 centrosomal protein 7 SLE vs 290 kDa HV 449 90861 HN1L hematological and 7 SLE vs neurological HV expressed 1-like 450 349136 WDR86 WD repeat domain 86 7 SLE vs HV no dsDNA dsDNA 7 SLE vs Gene ID HV 451 60 ACTB actin, beta 8 SLE vs HV 452 498 ATP5A1 ATP synthase, H+ 8 SLE vs transporting, HV mitochondrial F1 complex, alpha subunit 1, cardiac muscle 453 506 ATP5B ATP synthase, H+ 8 SLE vs transporting, HV mitochondrial F1 complex, beta polypeptide 454 563 AZGP1 alpha-2- 8 SLE vs glycoprotein 1, HV zinc-binding 455 602 BCL3 B-cell CLL/lymphoma 8 SLE vs 3 HV 456 1729 DIAPH1 diaphanous-related 8 SLE vs formin 1 HV 457 1937 EEF1G eukaryotic 8 SLE vs translation HV elongation factor 1 gamma 458 1973 EIF4A1 eukaryotic 8 SLE vs translation HV initiation factor 4A1 459 2280 FKBP1A FK506 binding 8 SLE vs protein 1A, 12 kDa HV 460 2495 FTH1 ferritin, heavy 8 SLE vs polypeptide 1 HV 461 2597 GAPDH glyceraldehyde-3- 8 SLE vs phosphate HV dehydrogenase 462 2819 GPD1 glycerol-3- 8 SLE vs phosphate HV dehydrogenase 1 (soluble) 463 3295 HSD17B4 hydroxysteroid (17- 8 SLE vs beta) dehydrogenase HV 4 464 3305 HSPA1L heat shock 70 kDa 8 SLE vs protein 1-like HV 465 3312 HSPA8 heat shock 70 kDa 8 SLE vs protein 8 HV 466 4174 MCM5 minichromosome 8 SLE vs maintenance complex HV component 5 467 4215 MAP3K3 mitogen-activated 8 SLE vs protein kinase HV kinase kinase 3 468 4591 TRIM37 tripartite motif 8 SLE vs containing 37 HV 469 4691 NCL nucleolin 8 SLE vs HV 470 4898 NRD1 nardilysin (N- 8 SLE vs arginine dibasic HV convertase) 471 4904 YBX1 Y box binding 8 SLE vs protein 1 HV 472 5037 PEBP1 phosphatidylethanol 8 SLE vs amine binding HV protein 1 473 5315 PKM2 pyruvate kinase, 8 SLE vs muscle HV 474 5481 PPID peptidylprolyl 8 SLE vs isomerase D HV 475 5684 PSMA3 proteasome 8 SLE vs (prosome, HV macropain) subunit, alpha type, 3 476 6128 RPL6 ribosomal protein 8 SLE vs L6 HV 477 6129 RPL7 ribosomal protein 8 SLE vs L7 HV 478 6130 RPL7A ribosomal protein 8 SLE vs L7a HV 479 6132 RPL8 ribosomal protein 8 SLE vs L8 HV 480 6187 RPS2 ribosomal protein 8 SLE vs S2 HV 481 6189 RPS3A ribosomal protein 8 SLE vs S3A HV 482 6249 CLIP1 CAP-GLY domain 8 SLE vs containing linker HV protein 1 483 6793 STK10 serine/threonine 8 SLE vs kinase 10 HV 484 6880 TAF9 TAF9 RNA polymerase 8 SLE vs II, TATA box HV binding protein (TBP)-associated factor, 32 kDa 485 7001 PRDX2 peroxiredoxin 2 8 SLE vs HV 486 7552 ZNF711 zinc finger protein 8 SLE vs 711 HV 487 8260 ARD1A N(alpha)- 8 SLE vs acetyltransferase HV 10, NatA catalytic subunit 488 8317 CDC7 cell division cycle 8 SLE vs 7 HV 489 8667 EIF3H eukaryotic 8 SLE vs translation HV initiation factor 3, subunit H 490 9223 MAGI1 membrane associated 8 SLE vs guanylate kinase, HV WW and PDZ domain containing 1 491 9230 RAB11B RAB11B, member RAS 8 SLE vs oncogene family HV 492 9425 CDYL chromodomain 8 SLE vs protein, Y-like HV 493 9694 EMC2 ER membrane protein 8 SLE vs complex subunit 2 HV 494 10075 HUWE1 HECT, UBA and WWE 8 SLE vs domain containing HV 1, E3 ubiquitin protein ligase 495 10109 ARPC2 actin related 8 SLE vs protein 2/3 HV complex, subunit 2, 34 kDa 496 10180 RBM6 RNA binding motif 8 SLE vs protein 6 HV 497 10273 STUB1 STIP1 homology and 8 SLE vs U-box containing HV protein 1, E3 ubiquitin protein ligase 498 10432 RBM14 RNA binding motif 8 SLE vs protein 14 HV 499 10539 GLRX3 glutaredoxin 3 8 SLE vs HV 500 10806 SDCCAG8 serologically 8 SLE vs defined colon HV cancer antigen 8 501 11108 PRDM4 PR domain 8 SLE vs containing 4 HV 502 23002 DAAM1 dishevelled 8 SLE vs associated HV activator of morphogenesis 1 503 23351 KHNYN KH and NYN domain 8 SLE vs containing HV 504 23589 CARHSP1 calcium regulated 8 SLE vs heat stable protein HV 1, 24 kDa 505 26986 PABPC1 poly(A) binding 8 SLE vs protein, HV cytoplasmic 1 506 27072 VPS41 vacuolar protein 8 SLE vs sorting 41 homolog HV (S. cerevisiae) 507 30836 DNTTIP2 deoxynucleotidyltrans- 8 SLE vs ferase, terminal, HV interacting protein 2 508 51028 VPS36 vacuolar protein 8 SLE vs sorting 36 homolog HV (S. cerevisiae) 509 51082 POLR1D polymerase (RNA) I 8 SLE vs polypeptide D, HV 16 kDa 510 51138 COPS4 COP9 signalosome 8 SLE vs subunit 4 HV 511 51466 EVL Enah/Vasp-like 8 SLE vs HV 512 54869 EPS8L1 EPS8-like 1 8 SLE vs HV 513 54903 MKS1 Meckel syndrome, 8 SLE vs type 1 HV 514 57017 COQ9 coenzyme Q9 8 SLE vs HV 515 57026 PDXP pyridoxal 8 SLE vs (pyridoxine, HV vitamin B6) phosphatase 516 57221 ARFGEF3 ARFGEF family 8 SLE vs member 3 HV 517 64753 CCDC136 coiled-coil domain 8 SLE vs containing 136 HV 518 80208 SPG11 spastic paraplegia 8 SLE vs 11 (autosomal HV recessive) 519 83858 ATAD3B ATPase family, AAA 8 SLE vs domain containing HV 3B 520 84893 FBXO18 F-box protein, 8 SLE vs helicase, 18 HV 521 129563 DIS3L2 DIS3 like 3′-5′ 8 SLE vs exoribonuclease 2 HV 522 144097 C11orf84 chromosome 11 open 8 SLE vs reading frame 84 HV 523 256364 EML3 echinorm 8 SLE vs microtubule HV associated protein like 3 524 347733 TUBB2B tubulin, beta 2B 8 SLE vs class IIb HV 525 3303 HSPA1A heat shock 70 kDa 8 SLE vs protein 1A HV 526 5163 PDK1 pyruvate 8 SLE vs dehydrogenase HV kinase, isozyme 1 527 1001 CDH3 cadherin 3, type 1, 8 SLE vs P-cadherin HV (placental)

Example 9 Identification of Autoantibody Reactivities in ENA-4-Negative SLE Patients

In order to identify new SLE-specific autoantigens, the autoantibody profiles of new SLE-specific autoantigens were the autoantibody profiles of the group of SLE patients seropositive for the autoantigens Sm-protein, U1-RNP, Rho52/SS-A and Ro60/SS-B, with which the seronegative was compared. The result of the statistical test is summarised in Table 2.

Group 4 comprises additional antigens suitable for the identification of ENA-4-negative SLE patients.

FIG. 5 shows the volcano plot of the autoantibody reactivities of ENA-4-positives compared to ENA-4-negative SLE patients.

Example 10 Calculation of Antigen Panels for Improved Diagnosis of SLE

Due to the high clinical and serological heterogeneity of the SLE disease, it is not possible to diagnose this disease using just one biomarker. It is therefore necessary to combine (where possible) uncorrelated biomarker panels to form what are known as biomarker panels.

Group 1 of the antigens in Table 2 comprises the most important 24 antigens used for the calculation of biomarker panels for the diagnosis of SLE.

Table 4 shows different combinations of antigens which were used for the calculation of the biomarker panels (ENA-4, ENA-4+anti-rib, PI, PII, PIII, PVI, PV).

FIG. 6 shows the sensitivity and specificity and also the area under the curve (AUC) for the known 4 antigens compared with antigen panels that were calculated using a combination of the antigens from Table 2. Due to the inclusion of the 3 ribosomal antigens anti-rib) RPLP0, RPLP1 and RPLP2, the sensitivity could be increased already by 10% compared with the known 4 ENA antigens from 0.63 to 0.72. However, only a freely selected combination of known and new antigens could increase the sensitivity by 20% compared with the ENA-4 test to 0.8.

Antigens which have an adjusted p-value for the non-parametric mean value comparison between groups of <0.05, alongside a fold change of >1.5 and additionally an AUC resulting from the ROC analysis of >0.75 were selected on the basis of the univariate results for the generation of panels. In addition, the ENA-4 antigens were selected. For this pool of selected candidates, an L1-penalised logistic regression model was established within the scope of a nested cross validation. Antigens which were not taken into consideration within the scope of the model formation were removed from the further consideration. Within the remaining pools, panel contents were defined, for example in accordance with established markers and new markers.

Group 4 in Table 2 contains further statistically significant antigens which can be used for the identification of ENA-4-negative patients and for the definition of biomarker panels.

Group 6 in Table 2 contains further statistically significant antigens which can be used for the diagnosis and differential diagnosis of SLE compared with healthy controls and other autoimmune diseases.

TABLE 4 Composition of the diagnostic SLE Panel Panels ENA-4 + Gene anti- Symbol Gene Name Antigen ENA-4 rib PI PII PIII PVI PV SNRPN small nuclear Sm X X X X SEQ ID ribonucleoprotein protein D NO. 14 polypeptide N TRIM21 tripartite motif- SSA/R0 X X X X X SEQ ID containing 21 NO. 19 TROVE2 TROVE domain family, SSA/Ro60 X X X X X SEQ ID member 2 NO. 20 SSB Sjogren syndrome SSB/La X X X X X SEQ ID antigen B NO. 17 (autoantigen La) SNRNP70 small nuclear U1-RNP X X X X X SEQ ID ribonucleoprotein NO. 12 70 kDa (U1) SNRPB small nuclear Sm X X X X X SEQ ID ribonucleoprotein protein NO. 13 polypeptides B and B/B′ B1 RPLP0 ribosomal protein, anti-rib X X X X SEQ ID large, P0 NO. 8 RPLP2 ribosomal protein, anti-rib X X X SEQ ID large, P2 NO. 10 RPLP1 ribosomal protein, anti-rib X X X SEQ ID large, P1 NO. 9 XRCC5 X-ray repair Ku80 X SEQ ID complementing NO. 22 defective repair in Chinese hamster cells 5 (double- strand-break rejoining) VIM vimentin X X SEQ ID NO. 21 SPTB spectrin, beta, X X SEQ ID erythrocytic NO. 16 DBT dihydrolipoamide X X X X X SEQ ID branched chain NO. 1 transacylase E2 EZR ezrin X X X X X SEQ ID NO. 3 HNRNPA2B1 heterogeneous X X SEQ ID nuclear NO. 6 ribonucleoprotein A2/B1 TMPO thymopoietin X X X X SEQ ID NO. 18 MVP major vault protein X X X X SEQ ID NO. 7 ZNF574 zinc finger protein X X X SEQ ID 574 NO. 24 HIST1H2BD histone cluster 1, anti- X X SEQ ID H2bd Histone NO. 4 SH3KBP1 SH3-domain kinase X SEQ ID binding protein 1 NO. 11 ZNF217 zinc finger protein X X SEQ ID 217 NO. 23 SP100 SP100 nuclear X X X X X SEQ ID antigen NO. 15 HNRNPA1 heterogeneous X X X X X SEQ ID nuclear NO. 5 ribonucleoprotein A1 DLAT dihydrolipoamide S- PDC-E2, X X X X SEQ ID acetyltransferase M2 NO. 2 antigen

TABLE 5 AUC, sensitivity and specificity of the SLE panels AUC CI (AUC) Sens. CI (Sens.) Spec. CI (Spec) a) SLE versus healthy controls SLE vs PSS Panel PI 0.99 [0.94, 0.98] 0.83 [0.77, 0.9] 0.98 [0.96, 1.0] Panel PII 0.90 [0.84, 0.95] 0.63 [0.53, 0.73] 0.94 [0.91, 0.98] Panel PIII 0.91 [0.87, 0.95] 0.61  [0.5, 0.72] 0.95 [0.92, 0.98] Panel PIV 0.90 [0.86, 0.94] 0.57 [0.44, 0.71] 0.95 [0.91, 0.99] Panel PV 0.91 [0.87, 0.96] 0.64 [0.52, 0.76] 0.95 [0.91, 0.99] ENA-4 0.89 [0.84, 0.94] 0.63 [0.49, 0.77] 0.96 [0.94, 0.98] ENA-4 + anti- 0.93 [0.88, 0.98] 0.72 [0.6, 0.84] 0.97 [0.95, 0.99] rib b) SLE versus SSc (PSS) Panel PI 0.9 [0.85, 0.95] 0.78 [0.73, 0.83] 0.83 [0.71, 0.94] Panel PII 0.83 [0.78, 0.88] 0.72 [0.61, 0.83] 0.76 [0.68, 0.85] Panel PIII 0.81 [0.74, 0.88] 0.68 [0.56, 0.79] 0.75  [0.6, 0.89] panel PIV 0.83 [0.78, 0.88] 0.69 [0.58, 0.81] 0.77 [0.67, 0.88] Panel PV 0.84 [0.79, 0.9] 0.71 [0.62, 0.8] 0.76 [0.65, 0.87] ENA-4 0.75 [0.66, 0.85] 0.6  [0.5, 0.7] 0.8 [0.71, 0.88] ENA-4 + anti- 0.82 [0.74, 0.9] 0.63 [0.51, 0.75] 0.83 [0.74, 0.93] rib c) SLE versus all AID (early RA, SSc, SPA) SLE vs Pool (EA, PSS, SPA) Panel PI 0.94 [0.91, 0.96] 0.6 [0.51, 0.69] 0.98 [0.98, 0.99] Panel PII 0.83 [0.78, 0.89] 0.26 [0.16, 0.35] 0.98 [0.97, 0.99] Panel PIII 0.83 [0.74, 0.92] 0.27 [0.16, 0.37] 0.99 [0.98, 1] Panel PIV 0.83 [0.79, 0.87] 0.19  [0.1, 0.28] 0.98 [0.97, 0.99] Panel PV 0.85 [0.78, 0.91] 0.34 [0.22, 0.46] 0.99 [0.98, 0.99] ENA-4 0.84 [0.79, 0.9] 0.35 [0.22, 0.47] 0.99 [0.98, 0.99] ENA-4 + anti- 0.91 [0.88, 0.93] 0.49 [0.41, 0.58] 0.98 [0.97, 0.99] rib

Example 11 Identification of Lupus Nephritis Patients

The autoantibody profiles of SLE patients with lupus nephritis were compared with those of SLE patients without lupus nephritis. Following univariate statistical evaluation, a threshold value of p<0.05 and a 1.5 times modified reactivity compared with the control group were applied. 85 antigens met these criteria and are detailed in Table 2.

FIG. 7 shows the volcano plot of the sera compared with selected lupus nephritis antigens.

Group 2 in Table 2 contains 30 additional and important antigens which can be used for the generation of lupus nephritis biomarker panels.

An L1-penalised logistic regression model with five-fold cross validation and twenty times repetition was computed for the selection of the best candidates. The antigens selected most frequently in this model computation with a frequency of more than 50% constituted the best candidates for the diagnosis of lupus nephritis.

FIG. 8 shows the frequency distribution of the lupus nephritis antigens.

Group 5 comprises further statistically significant antigens suitable for the diagnosis of lupus nephritis.

Example 12 Identification of SLE Subforms and Subgroups

The large clinical heterogeneity of SLE constitutes a big problem both for diagnosis and active substance development.

The identification of specific antibody signatures in SLE patient subgroups thus constitutes a key step for the improved definition of patient groups in clinical studies. By way of example, as presented under Example 9, specific antibodies for lupus nephritis could be used to recruit this subgroup for drug studies.

A large number of new active substances and therapeutic antibodies are currently undergoing clinical development: inter alia, therapeutic antibodies against cell-surface receptors of immune cells, such as anti-CD20, anti-CD22, or against pro-inflammatory cytokines, such as anti-IL6, are being developed. It is therefore now possible, due to the identification of serologically-defined subgroups of SLE, to link this to a target-specific response to a drug.

It was first examined whether, on the basis of the typical ENA antigens and ribosomal antigens, different autoantibody signatures can already be identified in SLE patients and thus patient subgroups.

FIGS. 9a and b show a dendogram of the SLE antigens after calculation of Spearman's rank correlation coefficient

FIG. 9a shows a dendogram for the antigens Sm, SS-B, Ro-52/SS-A, Ro60-SS-B and three ribosomal proteins.

3 antigen clusters can be already be defined on the basis of these 7 antigens.

For an improved definition of SLE subgroups, however, a larger number of antigens are necessary. 50 antigens from Table 2 were therefore selected, and the correlation thereof in SLE patients was examined by calculation of Spearman's rank correlation coefficient.

Group 3 contains 37 of the most important antigens necessary for the characterisation of SLE subgroups. Further antigens have already been defined in group 1 and group 2.

The presentation of the antigens as a dendogram shows groups of antigens of which the reactivities in SLE patients are correlated with one another.

As illustrated in FIG. 9b, at least 6 groups of correlated antigens can be identified as a result.

Interestingly, one of the clusters includes the antigens MVP, MIER2, CCS, DCAF6, which were identified in the table as biomarkers for lupus nephritis.

Due to the calculation of a PPLS-DA-based regression model, it is possible to visualise how well the selected antigens contribute to the discrimination of the SLE patients from healthy controls.

FIGS. 10a and b show the PPLS-DA biplot of the SLE patients and healthy controls with use of the SLE antigens.

FIG. 10a shows a PPLS-DA biplot for the selected ENA antigens and ribosomal proteins and measured values thereof in the SLE patients. FIG. 10a shows that the separation of healthy and SLE is not complete and that some SLE patients coincide with the group of healthy samples. However, there is already a division of the SLE patients into 2 clusters with just few antigens.

FIG. 10b shows a PPLS-DA biplot for 50 antigens which are contained in Table 2. The selection of further antigens results in a practically perfect separation of the SLE patients and healthy samples.

A further subdivision of the SLE patients into possible subgroups is provided by 50 antigens. These subgroups can be defined by specific antigens, some of which have been highlighted by way of example.

Example 13 Validation of SLE Antigens in an Independent Test Cohort II

For validation of the SLE-associated autoantigens specified in Table 2, the autoantibody reactivity in serum samples of a further independent cohort of 101 SLE patients, 105 healthy controls and 89 samples of the SLE cohort from Example 6 was measured. For this purpose the 529 human proteins specified in Table 2 (SEQ ID No. 1057 to 1584), and double-stranded DNA (dsDNA) thereof, were coupled to Luminex beads, and the antigen-coupled beads were measured in a multiplex assay with the patient samples. The binding of autoantibodies was measured by means of a PE-conjugated autoantibody in a Luminex instrument.

Following univariate statistical evaluation, a threshold value of p<0.05 (Wilcoxon rank-sum test) compared with the control group was applied.

A list of the significance values (p-values) for autoantibodies against 50 antigens in the SLE cohort II is shown in Table 6. Of the 50 antigens, 43 antigens in cohort I and cohort II achieved a p-value <0.05.

The frequency (in %) of autoantibodies against 50 antigens in the three SLE cohorts is shown in Table 7.

FIG. 11: shows the calculated p-value of the antigens from Table 2 and also the frequency of SLE patients who were classified as autoantibody-positive for this antigen.

Example 14 Validation of SLE Autoantigens in a Third Independent Test Cohort III

For validation of the SLE-associated autoantigens specified in Table 2, the autoantibody reactivity in serum samples of an independent cohort of 183 SLE patients and 109 healthy controls was measured. For this purpose, 6,912 human proteins were coupled to Luminex beads and the protein-coupled beads were measured in a multiplex assay with the patient samples. The binding of autoantibodies was measured by means of a PE-conjugated autoantibody in a Luminex instrument.

After univariate statistical evaluation, a threshold value of p<0.05 and a Cohen's d effect size of greater than 0.3 compared to the control group was provided.

A list of the significance values is shown in Table 6. The table contains selected markers which are part of the panels ENA+anti-rib, panel I, panel VI, panel VII and panel VIII.

The table contains further markers which achieved a p-value of <0.05 in all three cohorts.

TABLE 6 significance values (p-values) of 50 antigens in 3 SLE cohorts SLE SLE Seq. Gene SLE cohort cohort Nr GeneID Symbol cohort I II III Panel 1 1629 DBT 1.28E−04 2.16E−03 3.82E−03 Panel I; II; III; IV; V; VII 2 1737 DLAT 6.33E−08 4.12E−11 1.31E−04 Panel I; III; IV; VI; VII 3 7430 EZR 1.44E−03 2.68E−01 9.79E−02 panel I; II; III; IV 4 3017 HIST1H2BD 9.43E−01 4.08E−01 4.00E−02 Panel II, V 5 3178 HNRNPA1 1.99E−09 3.60E−06 2.81E−04 Panel I; II, III; IV; V; VI; VII 6 3181 HNRNPA2B1 7.31E−08 2.81E−05 1.70E−05 Panel III; V; VI; VII 7 9961 MVP 1.40E−03 3.90E−06 1.56E−04 Panel I; II; III; V; VI; VII 8 6175 RPLP0 4.59E−13 4.75E−12 3.51E−08 ENA-4 + anti-rib, Panel I; III; VI; VII 9 6176 RPLP1 4.61E−11 3.05E−13 7.50E−07 ENA-4 + anti-rib; Panel III; IV; VII 10 6181 RPLP2 2.38E−10 5.18E−10 2.94E−09 ENA-4 + anti-rib; Panel I; VI; VII 11 30011 SH3KBP1 1.68E−04 2.22E−08 2.64E−02 Panel V 12 6625 SNRNP70 4.87E−02 9.02E−02 1.22E−08 ENA-4 + anti-rib; Panel I; II; IV 13 6628 SNRPB 2.95E−09 5.57E−07 2.49E−09 ENA-4 + anti-rib; Panel I; II; IV; VI; VII 14 6638 SNRPN 7.44E−05 2.61E−02 3.64E−02 ENA-4 + anti-rib, Panel II; Panel IV 15 6672 SP100 1.98E−04 2.47E−04 3.04E−07 Panel I; II; III; IV; V; VII 16 6710 SPTB 7.76E−06 5.13E−01 8.37E−01 Panel III; V 17 6741 SSB 1.75E−03 3.20E−02 7.82E−02 ENA-4 + anti-rib; Panel I; II; IV 18 7112 TMPO 2.20E−03 3.15E−02 1.15E−05 Panel I; II; III; IV; VI 19 6737 TRIM21 5.07E−12 1.96E−10 6.35E−10 Panel I; II; iV; VI; VII 20 6738 TROVE2 6.11E−04 2.59E−01 9.27E−05 ENA-4 + anti-rib; Panel I; II; IV 21 7431 VIM 2.37E−01 2.25E−04 1.06E−03 Panel III; V 22 7520 XRCC5 2.06E−06 2.01E−05 7.83E−04 Panel V; VI; VII 23 7764 ZNF217 3.28E−01 1.55E−01 5.04E−05 Panel III; V 24 64763 ZNF574 1.02E−02 8.36E−04 1.33E−03 Panel I; II; V; VII 31 9973 CCS 6.65E−06 5.28E−06 6.62E−09 Panel VII 95 6629 SNRPB2 1.06E−03 8.68E−03 3.66E−06 Panel VIII 128 10970 CKAP4 1.52E−05 7.26E−08 4.60E−05 Panel VIII 134 1743 DLST 1.63E−05 1.78E−06 4.95E−05 Panel VII 168 4841 NONO 1.27E−04 3.76E−07 5.17E−04 Panel VI; VII 169 29982 NRBF2 2.22E−04 2.44E−02 7.44E−03 Panel VIII 171 4926 NUMA1 1.62E−03 4.28E−05 4.31E−03 Panel VIII 213 7791 ZYX 4.54E−04 1.77E−05 2.57E−03 Panel VII 367 4670 HNRNPM 7.61E−03 8.98E−03 2.34E−05 Panel VII 368 10540 DCTN2 1.11E−06 1.69E−08 2.49E−05 Panel VII 369 10938 EHD1 5.60E−05 1.73E−05 1.01E−03 Panel VII 371 684 BST2 2.51E−02 1.44E−02 1.13E−08 Panel VIII 372 1058 CENPA 4.45E−04 8.70E−06 2.51E−05 Panel VIII 374 3092 HIP1 4.42E−02 8.73E−07 2.03E−04 Panel VIII 375 3336 HSPE1 2.15E−02 1.42E−02 1.73E−03 Panel VIII 376 5455 POU3F3 1.31E−03 1.02E−04 6.18E−03 Panel VIII 379 6626 SNRPA 7.16E−12 1.85E−11 2.60E−16 Panel VIII 380 6631 SNRPC 1.42E−06 1.06E−07 3.73E−15 Panel VIII 381 6757 SSX2 2.40E−03 1.78E−02 2.09E−04 Panel VIII 383 10134 BCAP31 4.10E−02 1.04E−05 4.34E−08 Panel VIII 389 55727 BTBD7 3.33E−02 3.68E−04 1.79E−04 Panel VIII 427 4000 LMNA 1.59E−03 7.49E−04 3.41E−04 Panel VIII 428 4582 MUC1 1.35E−04 1.66E−05 6.29E−04 Panel VIII 430 5340 PLG 1.22E−03 1.64E−02 5.61E−03 Panel VIII 431 6525 SMTN 2.05E−03 1.53E−02 9.78E−03 Panel VIII 451 dsDNA dsDNA 1.65E−06 5.35E−17 NA dsDNA

TABLE 7 List of the frequency of SLE patients positively tested for autoantibodies in 3 independent cohorts. The frequency in % of individuals positively tested for autoantibodies from Table 6 was calculated by means of the 95% quantile of healthy controls. Proportion of SLE patients positively tested for autoantibodies (%) based on the 95% quantile of the control group SLE SLE Seq. Gene SLE cohort cohort Nr. GeneID Symbol cohort I II III Panel 1 1629 DBT 1.28E−04 2.16E−03 3.82E−03 Panel I; II; III; IV; V; VII 2 1737 DLAT 6.33E−08 4.12E−11 1.31E−04 Panel I; III; IV; VI; VII 3 7430 EZR 1.44E−03 2.68E−01 9.79E−02 panel I; II; III; IV 4 3017 HIST1H2BD 9.43E−01 4.08E−01 4.00E−02 Panel II, V 5 3178 HNRNPA1 1.99E−09 3.60E−06 2.81E−04 Panel I; II, III; IV; V; VI; VII 6 3181 HNRNPA2B1 7.31E−08 2.81E−05 1.70E−05 Panel III; V; VI; VII 7 9961 MVP 1.40E−03 3.90E−06 1.56E−04 Panel I; II; III; V; VI; VII 8 6175 RPLP0 4.59E−13 4.75E−12 3.51E−08 ENA-4 + anti-rib, Panel I; III; VI; VII 9 6176 RPLP1 4.61E−11 3.05E−13 7.50E−07 ENA-4 + anti-rib; Panel III; IV; VII 10 6181 RPLP2 2.38E−10 5.18E−10 2.94E−09 ENA-4 + anti-rib; Panel I; VI; VII 11 30011 SH3KBP1 1.68E−04 2.22E−08 2.64E−02 Panel V 12 6625 SNRNP70 4.87E−02 9.02E−02 1.22E−08 ENA-4 + anti-rib; Panel I; II; IV 13 6628 SNRPB 2.95E−09 5.57E−07 2.49E−09 ENA-4 + anti-rib; Panel I; II; IV; VI; VII 14 6638 SNRPN 7.44E−05 2.61E−02 3.64E−02 ENA-4 + anti-rib, Panel II; Panel IV 15 6672 SP100 1.98E−04 2.47E−04 3.04E−07 Panel I; II; III; IV; V; VII 16 6710 SPTB 7.76E−06 5.13E−01 8.37E−01 Panel III; V 17 6741 SSB 1.75E−03 3.20E−02 7.82E−02 ENA-4 + anti-rib; Panel I; II; IV 18 7112 TMPO 2.20E−03 3.15E−02 1.15E−05 Panel I; II; III; IV; VI 19 6737 TRIM21 5.07E−12 1.96E−10 6.35E−10 Panel I; II; iV; VI; VII 20 6738 TROVE2 6.11E−04 2.59E−01 9.27E−05 ENA-4 + anti-rib; Panel I; II; IV 21 7431 VIM 2.37E−01 2.25E−04 1.06E−03 Panel III; V 22 7520 XRCC5 2.06E−06 2.01E−05 7.83E−04 Panel V; VI; VII 23 7764 ZNF217 3.28E−01 1.55E−01 5.04E−05 Panel III; V 24 64763 ZNF574 1.02E−02 8.36E−04 1.33E−03 Panel I; II; V; VII 31 9973 CCS 6.65E−06 5.28E−06 6.62E−09 Panel VII 95 6629 SNRPB2 1.06E−03 8.68E−03 3.66E−06 Panel VIII 128 10970 CKAP4 1.52E−05 7.26E−08 4.60E−05 Panel VIII 134 1743 DLST 1.63E−05 1.78E−06 4.95E−05 Panel VII 168 4841 NONO 1.27E−04 3.76E−07 5.17E−04 Panel VI; VII 169 29982 NRBF2 2.22E−04 2.44E−02 7.44E−03 Panel VIII 171 4926 NUMA1 1.62E−03 4.28E−05 4.31E−03 Panel VIII 213 7791 ZYX 4.54E−04 1.77E−05 2.57E−03 Panel VII 367 4670 HNRNPM 7.61E−03 8.98E−03 2.34E−05 Panel VII 368 10540 DCTN2 1.11E−06 1.69E−08 2.49E−05 Panel VII 369 10938 EHD1 5.60E−05 1.73E−05 1.01E−03 Panel VII 371 684 BST2 2.51E−02 1.44E−02 1.13E−08 Panel VIII 372 1058 CENPA 4.45E−04 8.70E−06 2.51E−05 Panel VIII 374 3092 HIP1 4.42E−02 8.73E−07 2.03E−04 Panel VIII 375 3336 HSPE1 2.15E−02 1.42E−02 1.73E−03 Panel VIII 376 5455 POU3F3 1.31E−03 1.02E−04 6.18E−03 Panel VIII 379 6626 SNRPA 7.16E−12 1.85E−11 2.60E−16 Panel VIII 380 6631 SNRPC 1.42E−06 1.06E−07 3.73E−15 Panel VIII 381 6757 SSX2 2.40E−03 1.78E−02 2.09E−04 Panel VIII 383 10134 BCAP31 4.10E−02 1.04E−05 4.34E−08 Panel VIII 389 55727 BTBD7 3.33E−02 3.68E−04 1.79E−04 Panel VIII 427 4000 LMNA 1.59E−03 7.49E−04 3.41E−04 Panel VIII 428 4582 MUC1 1.35E−04 1.66E−05 6.29E−04 Panel VIII 430 5340 PLG 1.22E−03 1.64E−02 5.61E−03 Panel VIII 431 6525 SMTN 2.05E−03 1.53E−02 9.78E−03 Panel VIII dsDNA dsDNA 1.65E−06 5.35E−17 NA dsDNA

Example Calculation of Biomarker Panels

As shown in Table 7, only at most approximately 60% of the SLE patients had antibodies for a specific autoantigen. In order to therefore increase the sensitivity of the diagnostic autoantibodies, such as anti-dsDNA, SSA-Ro (TRIM21/TROVE2) and U1-RNP (SNRNP70, SNRPNA, SNRNPC), new methods with which autoantibodies can be combined to form what are known as biomarker panels were tested.

For this pool of selected candidates, a logistic regression was carried out for panels PI to PVII. An L1-penalised logistic regression model was established within the scope of a nested cross validation for panels PVIII to PXI. Antigens which were not considered within the scope of the model formation were removed from the further consideration. The content of panels was defined within the remaining pool, for example in accordance with established markers and new markers.

The antigens specified in Table 2 were used for the calculation of biomarker panels for the diagnosis of SLE.

Table 4 shows different combinations of antigens which were used for the calculation of the biomarker panels (ENA-4, ENA-4+anti-rib, PI, PII, PIII, PVI, PV).

Table 8 shows further different combinations of antigens which were used for the calculation of panels and which were selected on account of their significance and reactivity in three SLE cohorts.

TABLE 8 Combinations of antigens from Table 2: Seq. ID Gene Panel Panel Panel Panel Panel Panel Panel Panel Panel Panel Nr GeneID Symbol ENA-4 +anti-rib PI PII PIII PIV PV VI VII VIII IX Panel X* Panel XI* 1 1629 DBT x x x x x x x x x x 2 1737 DLAT x x x x x x x x x x 5 3178 HNRNPA1 x x x x x x x x x x x 6 3181 HNRNPA2B1 x x x x x x x x 7 9961 MVP x x x x x x x x x x 8 6175 RPLP0 x x x x x x x x x x 9 6176 RPLP1 x x x x x x x x 10 6181 RPLP2 x x x x x x x x x x 13 6628 SNRPB x x x x x x x x x x x 15 6672 SP100 x x x x x x x x x x 19 6737 TRIM21 x x x x x x x x x x x 22 7520 XRCC5 x x x x x x x 24 64763 ZNF574 x x x x x x x x 134 1743 DLST x x x x x 168 4841 NONO x x x x x x 213 7791 ZYX x x x x x 367 4670 HNRNPM x x x x x 368 10540 DCTN2 x x x x x 369 10938 EHD1 x x x x x 4 3017 HIST1H2BD x x x x x x 12 6625 SNRNP70 x x x x x x x x x 17 6741 SSB x x x x x x x x x 18 7112 TMPO x x x x x x x x x x 20 6738 TROVE2 x x x x x x x x x 21 7431 VIM x x x x x x 23 7764 ZNF217 x x x x x x 29 9478 CABP1 x x x x 31 9973 CCS x x x x 46 4869 NPM1 x x x x 95 6629 SNRPB2 x x x x 128 10970 CKAP4 x x x x 136 51143 DYNC1LI1 x x x x 143 23360 FNBP4 x x x x 163 4688 NCF2 x x x x 169 29982 NRBF2 x x x x 171 4926 NUMA1 x x x x 188 644096 SDHAF1 x x x x 348 56674 TMEM9B x x x x 370 38 ACAT1 x x x x 371 684 BST2 x x x x 372 1058 CENPA x x x x 373 1665 DHX15 x x x x 374 3092 HIP1 x x x x 375 3336 HSPE1 x x x x 376 5455 POU3F3 x x x x 377 5918 RARRES1 x x x x 378 6136 RPL12 x x x x 379 6626 SNRPA x x x x 380 6631 SNRPC x x x x 381 6757 SSX2 x x x x 382 9788 MTSS1 x x x x 383 10134 BCAP31 x x x x 384 10522 DEAF1 x x x x 385 10633 RASL10A x x x x 386 54795 TRPM4 x x x x 387 54913 RPP25 x x x x 388 54994 C20orf11 x x x x 389 55727 BTBD7 x x x x 390 79140 CCDC28B x x x x 391 79613 TMCO7 x x x x 423 972 CD74 x x x x 424 1397 CRIP2 x x x x 425 2040 STOM x x x x 426 2316 FLNA x x x x 427 4000 LMNA x x x x 428 4582 MUC1 x x x x 429 5230 PGK1 x x x x 430 5340 PLG x x x x 431 6525 SMTN x x x x 432 8936 WASF1 x x x x 433 23647 ARFIP2 x x x x 3 7430 EZR x x x x x x x x 11 30011 SH3KBP1 x x x x 14 6638 SNRPN x x x x x x x 16 6710 SPTB x x x x x 33 55802 DCP1A x x x 41 54531 MIER2 x x x 48 11040 PIM2 x x x 74 10933 MORF4L1 x x x 105 8615 USO1 x x x 108 375690 WASH5P x x x 114 55256 ADI1 x x x 115 9255 AIMP1 x x x 116 54522 ANKRD16 x x x 132 8642 DCHS1 x x x 140 100129583 FAM47E x x x 145 64689 GORASP1 x x x 152 23135 KDM6B x x x 166 22861 NLRP1 x x x 170 8439 NSMAF x x x 174 5195 PEX14 x x x 186 8578 SCARF1 x x x 191 6421 SFPQ x x x 197 54961 SSH3 x x x 202 90326 THAP3 x x x 255 55740 ENAH x x x 263 150946 FAM59B x x x 277 3304 HSPA1B x x x 292 4137 MAPT x x x 331 4736 RPL10A x x x 343 23345 SYNE1 x x x 350 10155 TRIM28 x x x 358 65109 UPF3B x x x 392 5504 PPP1R2 x x x 393 8349 HIST2H2BE x x x 394 11168 PSIP1 x x x 395 149986 LSM14B x x x 434 6712 SPTBN2 x x x 435 6729 SRP54 x x x 436 9987 HNRPDL x x x *The panels X and XI can be supplemented by 20 or more markers from the other available 1587 markers, in particular proteins.

Panel VI comprises 11 antigens which were measured in all three SLE cohorts with a p-value <0.05.

Panel VII comprises 19 antigens which were measured in the three SLE cohorts with a p-value <0.05.

Panel VIII comprises panel VII and a further 52 antigens which were found in cohort 3 and at least one of the other SLE cohorts with a p-value <0.05 for the comparison of SLE against healthy controls.

Panel IX comprises panel VII, panel VIII and a further 110 antigens which, in one or two SLE cohorts for the comparison of SLE against healthy controls, achieved a p-value of 0.05.

Panel X comprises panel VII, panel VIII, panel IX and a further 227 antigens which, as specified in Table 2, originate from different comparisons and achieved a p-value <0.05 in at least one SLE cohort.

Tables 9a, 9c and 9e show the area under the curve (AUC) confidence interval, sensitivity and specificity of different biomarker combinations in the three different SLE cohorts.

Tables 9b and 9d show the area under the curve (AUC), confidence interval, sensitivity and specificity of the different panels in the three SLE cohorts in combination with anti-dsDNA autoantibodies.

TABLE 9a Area under the curve (AUC), sensitivity and specificity of the different panels in the SLE cohort I. AUC Sensitivity Specificity Cohort I lower upper lower lower Panel mean CI CI mean CI upper CI mean CI upper CI PI 0.86 0.84 0.87 0.79 0.76 0.81 0.84 0.82 0.86 PII 0.88 0.87 0.90 0.81 0.79 0.84 0.82 0.80 0.85 PIII 0.84 0.83 0.86 0.74 0.71 0.76 0.80 0.77 0.83 PIV 0.85 0.84 0.87 0.80 0.77 0.82 0.83 0.81 0.85 PV 0.81 0.79 0.83 0.73 0.70 0.75 0.76 0.73 0.79 PVI 0.87 0.86 0.89 0.79 0.77 0.82 0.83 0.81 0.85 Panel.ENA 0.87 0.85 0.88 0.73 0.71 0.76 0.86 0.84 0.89 Panel.ENA + 0.87 0.85 0.88 0.78 0.75 0.80 0.83 0.81 0.85 antiRib PVII 0.79 0.77 0.81 0.75 0.72 0.78 0.77 0.74 0.79 PVIII 0.85 0.83 0.86 0.75 0.72 0.78 0.82 0.79 0.84 PIX 0.83 0.81 0.84 0.73 0.71 0.76 0.81 0.78 0.83 PX 0.83 0.81 0.84 0.73 0.70 0.76 0.78 0.76 0.81 PXI 0.83 0.81 0.84 0.74 0.71 0.76 0.79 0.76 0.81

TABLE 9b Area under the curve (AUC), upper and lower confidence interval (CI), sensitivity and specificity of the biomarker panels in SLE cohort I in combination with anti- dsDNA autoantibodies. Cohort I Panel AUC Sensitivity Specificity plus lower upper lower lower dsDNA mean CI CI mean CI upper CI mean CI upper CI PI 0.86 0.84 0.87 0.79 0.77 0.81 0.83 0.81 0.85 PII 0.87 0.85 0.88 0.80 0.77 0.82 0.81 0.79 0.83 PIII 0.83 0.81 0.85 0.74 0.71 0.77 0.78 0.76 0.81 PIV 0.86 0.84 0.87 0.79 0.76 0.82 0.83 0.81 0.85 PV 0.80 0.78 0.82 0.72 0.70 0.75 0.76 0.73 0.78 PVI 0.86 0.85 0.88 0.79 0.77 0.82 0.82 0.80 0.85 Panel.ENA 0.86 0.85 0.88 0.73 0.71 0.76 0.86 0.84 0.89 Panel.ENA + 0.86 0.85 0.88 0.76 0.74 0.78 0.83 0.80 0.85 antiRib PVII 0.79 0.77 0.81 0.74 0.71 0.77 0.76 0.73 0.78 PVIII 0.89 0.88 0.90 0.80 0.78 0.83 0.85 0.83 0.87 PIX 0.90 0.89 0.92 0.81 0.79 0.83 0.85 0.83 0.87 PX 0.84 0.82 0.86 0.73 0.70 0.75 0.81 0.79 0.84 PXI 0.89 0.88 0.90 0.81 0.78 0.83 0.84 0.82 0.86

TABLE 9c Area under the curve (AUC), shows the sensitivity and specificity of the different panels in the SLE cohort II. Cohort AUC Sensitivity Specificity II lower upper lower lower Panel mean CI CI mean CI upper CI mean CI upper CI PI 0.84 0.83 0.86 0.74 0.72 0.76 0.79 0.77 0.81 PII 0.78 0.77 0.80 0.68 0.65 0.70 0.72 0.70 0.75 PIII 0.83 0.81 0.84 0.73 0.70 0.75 0.78 0.76 0.81 PIV 0.86 0.84 0.87 0.76 0.74 0.78 0.81 0.79 0.84 PV 0.77 0.75 0.78 0.67 0.65 0.69 0.74 0.72 0.76 PVI 0.87 0.86 0.88 0.77 0.74 0.79 0.82 0.80 0.84 Panel.ENA 0.76 0.74 0.77 0.59 0.56 0.61 0.78 0.75 0.80 Panel.ENA + 0.84 0.83 0.86 0.73 0.71 0.76 0.83 0.82 0.85 antiRib PVII 0.84 0.82 0.86 0.76 0.74 0.78 0.80 0.77 0.82 PVIII 0.85 0.83 0.86 0.76 0.74 0.78 0.80 0.78 0.82 PIX 0.84 0.83 0.86 0.76 0.74 0.78 0.79 0.77 0.81 PX 0.83 0.81 0.85 0.76 0.73 0.78 0.78 0.76 0.80 PXI 0.82 0.81 0.84 0.74 0.71 0.76 0.79 0.76 0.81

TABLE 9d Area under the curve (AUC), sensitivity and specificity of the different panels in SLE cohort II in combination with anti-dsDNA autoantibodies. Cohort II Panel AUC Sensitivity Specificity plus lower upper lower lower dsDNA mean CI CI mean CI upper CI mean CI upper CI PI 0.84 0.82 0.85 0.73 0.71 0.76 0.78 0.76 0.81 PII 0.78 0.76 0.80 0.67 0.65 0.70 0.73 0.70 0.75 PIII 0.82 0.81 0.84 0.73 0.71 0.75 0.76 0.74 0.79 PIV 0.85 0.84 0.87 0.76 0.73 0.78 0.80 0.78 0.83 PV 0.77 0.75 0.78 0.67 0.65 0.69 0.71 0.69 0.74 PVI 0.87 0.85 0.88 0.77 0.75 0.79 0.82 0.80 0.84 Panel.ENA 0.77 0.76 0.79 0.60 0.58 0.63 0.77 0.75 0.80 Panel.ENA + 0.85 0.84 0.86 0.73 0.71 0.76 0.83 0.81 0.85 antiRib PVII 0.84 0.82 0.85 0.75 0.73 0.78 0.79 0.77 0.82 PVIII 0.85 0.83 0.86 0.72 0.70 0.75 0.83 0.80 0.85 PIX 0.78 0.77 0.80 0.64 0.62 0.67 0.78 0.75 0.80 PX 0.84 0.83 0.85 0.72 0.70 0.75 0.83 0.81 0.85 PXI 0.87 0.85 0.88 0.75 0.73 0.77 0.84 0.82 0.86

TABLE 9e Area under the curve (AUC), sensitivity and specificity of the different panels in the SLE cohort III. Cohort AUC Sensitivity Specificity III lower upper lower lower Panel mean CI CI mean CI upper CI mean CI upper CI PI 0.83 0.82 0.84 0.71 0.69 0.73 0.80 0.78 0.81 PII 0.82 0.81 0.84 0.71 0.69 0.72 0.80 0.79 0.81 PIII 0.79 0.78 0.80 0.65 0.63 0.67 0.76 0.74 0.78 PIV 0.82 0.81 0.83 0.71 0.69 0.73 0.79 0.78 0.81 PV 0.77 0.76 0.78 0.66 0.64 0.67 0.76 0.74 0.78 PVI 0.84 0.83 0.85 0.71 0.70 0.73 0.81 0.79 0.82 Panel.ENA 0.78 0.77 0.80 0.65 0.63 0.67 0.82 0.81 0.84 Panel.ENA + 0.79 0.78 0.80 0.67 0.66 0.69 0.83 0.82 0.85 antiRib PVII 0.83 0.82 0.84 0.72 0.71 0.74 0.79 0.77 0.81 PVIII 0.83 0.82 0.84 0.73 0.72 0.75 0.77 0.76 0.79 PIX 0.81 0.79 0.82 0.72 0.70 0.74 0.76 0.74 0.77 PX 0.79 0.78 0.81 0.73 0.71 0.75 0.76 0.74 0.78 PXI 0.78 0.77 0.80 0.70 0.69 0.72 0.75 0.73 0.77

FIG. 11: The figure shows the comparison of the calculated p-values and autoantibody frequencies (% positive classified observations) for the antigens from Table 2 in the three SLE cohorts. The antigens are illustrated as circles with the consecutive number. The horizontal line marks the threshold value of p<0.05 for the comparison of SLE compared with healthy controls.

LITERATURE

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Claims

1. A method for identifying markers for systemic lupus erythematosus (SLE), comprising:

a) bringing serum samples of SLE patients into contact with more than 5000 antigens coupled to beads, measuring the binding of each individual antigen to autoantibodies in the serum samples of the SLE patients using an immunofluorescence assay, and determining the median fluorescence intensity (MFI) for each individual antigen;
b) bringing serum samples of patients with rheumatoid arthritis (RA) into contact with the more than 5000 antigens coupled to beads, measuring the binding of each individual antigen to autoantibodies in the serum samples of the RA patients using said immunofluorescence assay, and determining from this—the median fluorescence intensity (MFI) for each individual antigen;
c) bringing serum samples of healthy individuals into contact with the more than 5000 antigens coupled to beads, measuring the binding of each individual antigen to autoantibodies in the serum samples of the healthy individuals using said immunofluorescence assay, and determining the median fluorescence intensity (MFI) for each individual antigen;
d) statistically evaluating the MFI for each individual antigen obtained from a), b), and c) using a univariate analysis and identifying marker candidate antigens with which SLE patients can be differentiated from RA patients and from healthy individuals;
e) bringing serum samples of patients with early RA into contact with the marker candidate antigens identified in d) coupled to beads, measuring the binding of each individual marker candidate antigens to autoantibodies in the serum samples of patients with early RA using said immunofluorescence assay, and determining the median fluorescence intensity (MFI) for each individual marker candidate antigen;
f) bringing serum samples of patients with systemic sclerosis (SSc) into contact with the marker candidate antigens identified in d) coupled to beads, measuring the binding of each marker candidate antigen to autoantibodies in the serum samples of SSc patients using said immunofluorescence assay, and determining the median fluorescence intensity (MFI) for each individual marker candidate antigen;
g) bringing serum samples of patients with ankylosing spondylitis or Bekhterev's disease (SPA) into contact with the marker candidate antigens identified in d) coupled to beads, measuring the binding of each marker candidate antigen to autoantibodies in the serum samples of SPA patients using said immunofluorescence assay, and determining the median fluorescence intensity (MFI) for each individual marker candidate antigen;
h) statistically evaluating the MFI for each individual marker candidate antigen obtained from e), f), and g) using an univariate analysis and identifying a marker for SLE when a threshold value of 3 standard deviations above the mean value of the healthy samples is not reached; and
i) identifying a SLE patient for stratification and administering at least one therapeutic agent to the SLE patient for treatment or monitoring the SLE patient for control of the SLE patient's therapy; wherein the marker for SLE is selected from the sequences of SEQ ID NO: 1-11, 13, 15, 16, 18, 19, 20-24, 28, 29, 31, 46, 61, 95, 126, 128, 134, 136, 143, 152, 163, 169, 171, 173, 188, 191, 213, 214, 241, 258, 270, 302, 348, 349, 367-370, 372-375, 378-391, 403, 406, 408, 415, and 423-433.

2. The method of claim 1 for identifying markers for SLE, comprising selecting a marker for SLE which, in the univariate analysis, has an adjusted p-value for the non-parametric mean value comparison between the groups of less than 0.05 and at the same time have a fold change of greater than 1.5 and an AUC resulting from the ROC analysis of greater than 0.75.

3. The method of claim 1, wherein the marker for SLE is selected from proteins encoded by SEQ ID NO: 1-11, 13, 15, 16, 18, 19, 20-24, 28, 29, 31, 46, 61, 95, 126, 128, 134, 136, 143, 152, 163, 169, 171, 173, 188, 191, 213, 214, 241, 258, 270, 302, 348, 349, 367-370, 372-375, 378-391, 403, 406, 408, 415, and 423-433.

4. The method of claim 2, wherein the marker for SLE is selected from proteins encoded by SEQ ID NO: 1-11, 13, 15, 16, 18, 19, 20-24, 28, 29, 31, 46, 61, 95, 126, 128, 134, 136, 143, 152, 163, 169, 171, 173, 188, 191, 213, 214, 241, 258, 270, 302, 348, 349, 367-370, 372-375, 378-391, 403, 406, 408, 415, and 423-433.

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Patent History
Patent number: 10746735
Type: Grant
Filed: Feb 10, 2015
Date of Patent: Aug 18, 2020
Patent Publication Number: 20170074875
Assignee: Oncimmune Germany GmbH (Dortmund)
Inventors: Angelika Lüking (Bochum), Peter Schulz-Knappe (Hemmingen), Carmen Theek (Herdecke), Petra Budde (Dortmund), Anna Telaar (Dortmund)
Primary Examiner: Changhwa J Cheu
Application Number: 15/117,508
Classifications
Current U.S. Class: Non/e
International Classification: G01N 33/564 (20060101);